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Sample records for adaptive intrusion data systems

  1. Adaptive intrusion data system

    International Nuclear Information System (INIS)

    Johnson, C.S.

    1976-01-01

    An Adaptive Intrusion Data System (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique digital data compression, storage, and formatting system. It also incorporates capability for video selection and recording for assessment of the sensors monitored by the system. The system is software reprogrammable to numerous configurations that may be utilized for the collection of environmental, bi-level, analog and video data. The output of the system is digital tapes formatted for direct data reduction on a CDC 6400 computer, and video tapes containing timed tagged information that can be correlated with the digital data

  2. Adaptive Intrusion Data System (AIDS)

    International Nuclear Information System (INIS)

    Corlis, N.E.

    1980-05-01

    The adaptive intrusion data system (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique data system which uses computer controlled data systems, video cameras and recorders, analog-to-digital conversion, environmental sensors, and digital recorders to collect sensor data. The data can be viewed either manually or with a special computerized data-reduction system which adds new data to a data base stored on a magnetic disc recorder. This report provides a synoptic account of the AIDS as it presently exists. Modifications to the purchased subsystems are described, and references are made to publications which describe the Sandia-designed subsystems

  3. Adaptive intrusion data system (AIDS) software routines

    International Nuclear Information System (INIS)

    Corlis, N.E.

    1980-07-01

    An Adaptive Intrusion Data System (AIDS) was developed to collect information from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique digital data-compression, storage, and formatting system; it also incorporates a capability for video selection and recording for assessment of the sensors monitored by the system. The system is software reprogrammable to numerous configurations that may be used for the collection of environmental, bilevel, analog, and video data. This report describes the software routines that control the different AIDS data-collection modes, the diagnostic programs to test the operating hardware, and the data format. Sample data printouts are also included

  4. Mass memory formatter subsystem of the adaptive intrusion data system

    International Nuclear Information System (INIS)

    Corlis, N.E.

    1980-09-01

    The Mass Memory Formatter was developed as part of the Adaptive Intrusion Data System (AIDS) to control a 2.4-megabit mass memory. The data from a Memory Controlled Processor is formatted before it is stored in the memory and reformatted during the readout mode. The data is then transmitted to a NOVA 2 minicomputer-controlled magnetic tape recorder for storage. Techniques and circuits are described

  5. Description, operation, and diagnostic routines for the adaptive intrusion data system

    International Nuclear Information System (INIS)

    Corlis, N.E.; Johnson, C.S.

    1978-03-01

    An Adaptive Intrusion Data System (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique digital data compression, storage, and formatting system. It also incorporates a capability for video selection and recording for assessment of the sensors monitored by the system. The system is software reprogrammable to numerous configurations that may be utilized for the collection of environmental, bi-metal, analog, and video data. This manual covers the procedures for operating AIDS. Instructions are given to guide the operator in software programming and control option selections required to program AIDS for data collection. Software diagnostic programs are included in this manual as a method of isolating system problems

  6. An Adaptive Database Intrusion Detection System

    Science.gov (United States)

    Barrios, Rita M.

    2011-01-01

    Intrusion detection is difficult to accomplish when attempting to employ current methodologies when considering the database and the authorized entity. It is a common understanding that current methodologies focus on the network architecture rather than the database, which is not an adequate solution when considering the insider threat. Recent…

  7. Autonomic intrusion detection: Adaptively detecting anomalies over unlabeled audit data streams in computer networks

    KAUST Repository

    Wang, Wei

    2014-06-22

    In this work, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-managing: self-labeling, self-updating and self-adapting. Our framework employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies. Two large real HTTP traffic streams collected in our institute as well as a set of benchmark KDD’99 data are used to validate the framework and the method. The test results show that the autonomic model achieves better results in terms of effectiveness and efficiency compared to adaptive Sequential Karhunen–Loeve method and static AP as well as three other static anomaly detection methods, namely, k-NN, PCA and SVM.

  8. Effective approach toward Intrusion Detection System using data mining techniques

    Directory of Open Access Journals (Sweden)

    G.V. Nadiammai

    2014-03-01

    Full Text Available With the tremendous growth of the usage of computers over network and development in application running on various platform captures the attention toward network security. This paradigm exploits security vulnerabilities on all computer systems that are technically difficult and expensive to solve. Hence intrusion is used as a key to compromise the integrity, availability and confidentiality of a computer resource. The Intrusion Detection System (IDS plays a vital role in detecting anomalies and attacks in the network. In this work, data mining concept is integrated with an IDS to identify the relevant, hidden data of interest for the user effectively and with less execution time. Four issues such as Classification of Data, High Level of Human Interaction, Lack of Labeled Data, and Effectiveness of Distributed Denial of Service Attack are being solved using the proposed algorithms like EDADT algorithm, Hybrid IDS model, Semi-Supervised Approach and Varying HOPERAA Algorithm respectively. Our proposed algorithm has been tested using KDD Cup dataset. All the proposed algorithm shows better accuracy and reduced false alarm rate when compared with existing algorithms.

  9. Interior intrusion detection systems

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez, J.R.; Matter, J.C. (Sandia National Labs., Albuquerque, NM (United States)); Dry, B. (BE, Inc., Barnwell, SC (United States))

    1991-10-01

    The purpose of this NUREG is to present technical information that should be useful to NRC licensees in designing interior intrusion detection systems. Interior intrusion sensors are discussed according to their primary application: boundary-penetration detection, volumetric detection, and point protection. Information necessary for implementation of an effective interior intrusion detection system is presented, including principles of operation, performance characteristics and guidelines for design, procurement, installation, testing, and maintenance. A glossary of sensor data terms is included. 36 figs., 6 tabs.

  10. Interior intrusion detection systems

    International Nuclear Information System (INIS)

    Rodriguez, J.R.; Matter, J.C.; Dry, B.

    1991-10-01

    The purpose of this NUREG is to present technical information that should be useful to NRC licensees in designing interior intrusion detection systems. Interior intrusion sensors are discussed according to their primary application: boundary-penetration detection, volumetric detection, and point protection. Information necessary for implementation of an effective interior intrusion detection system is presented, including principles of operation, performance characteristics and guidelines for design, procurement, installation, testing, and maintenance. A glossary of sensor data terms is included. 36 figs., 6 tabs

  11. Comparative study of adaptive-noise-cancellation algorithms for intrusion detection systems

    International Nuclear Information System (INIS)

    Claassen, J.P.; Patterson, M.M.

    1981-01-01

    Some intrusion detection systems are susceptible to nonstationary noise resulting in frequent nuisance alarms and poor detection when the noise is present. Adaptive inverse filtering for single channel systems and adaptive noise cancellation for two channel systems have both demonstrated good potential in removing correlated noise components prior detection. For such noise susceptible systems the suitability of a noise reduction algorithm must be established in a trade-off study weighing algorithm complexity against performance. The performance characteristics of several distinct classes of algorithms are established through comparative computer studies using real signals. The relative merits of the different algorithms are discussed in the light of the nature of intruder and noise signals

  12. Anomaly-Based Intrusion Detection Systems Utilizing System Call Data

    Science.gov (United States)

    2012-03-01

    2.1.1 Viruses The first use of the term “computer virus ” is attributed to Fred Cohen in 1983. Fred Cohen originally defined a computer virus as a...agents. Once compromised, these systems become part of what is known as a “zombie” network. 2.1.3 Trojans A Trojan horse is malware pretending to...be benign or useful software. When activated, Trojans perform unauthorized actions such as collecting, modifying, and forging data. Unlike viruses

  13. Intrusion detection system elements

    International Nuclear Information System (INIS)

    Eaton, M.J.; Mangan, D.L.

    1980-09-01

    This report highlights elements required for an intrusion detection system and discusses problems which can be encountered in attempting to make the elements effective. Topics discussed include: sensors, both for exterior detection and interior detection; alarm assessment systems, with the discussion focused on video assessment; and alarm reporting systems, including alarm communication systems and dislay/console considerations. Guidance on careful planning and design of a new or to-be-improved system is presented

  14. Interior intrusion alarm systems

    International Nuclear Information System (INIS)

    Prell, J.A.

    1978-01-01

    In meeting the requirements for the safeguarding of special nuclear material and the physical protection of licensed facilities, the licensee is required to design a physical security system that will meet minimum performance requirements. An integral part of any physical security system is the interior intrusion alarm system. The purpose of this report is to provide the potential user of an interior intrusion alarm system with information on the various types, components, and performance capabilities available so that he can design and install the optimum alarm system for his particular environment. In addition, maintenance and testing procedures are discussed and recommended which, if followed, will help the user obtain the optimum results from his system

  15. A Comparative Study of Data Mining Algorithms for High Detection Rate in Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Nabeela Ashraf

    2018-01-01

    Full Text Available Due to the fast growth and tradition of the internet over the last decades, the network security problems are increasing vigorously. Humans can not handle the speed of processes and the huge amount of data required to handle network anomalies. Therefore, it needs substantial automation in both speed and accuracy. Intrusion Detection System is one of the approaches to recognize illegal access and rare attacks to secure networks. In this proposed paper, Naive Bayes, J48 and Random Forest classifiers are compared to compute the detection rate and accuracy of IDS. For experiments, the KDD_NSL dataset is used.

  16. Idaho National Laboratory Supervisory Control and Data Acquisition Intrusion Detection System (SCADA IDS)

    Energy Technology Data Exchange (ETDEWEB)

    Jared Verba; Michael Milvich

    2008-05-01

    Current Intrusion Detection System (IDS) technology is not suited to be widely deployed inside a Supervisory, Control and Data Acquisition (SCADA) environment. Anomaly- and signature-based IDS technologies have developed methods to cover information technology-based networks activity and protocols effectively. However, these IDS technologies do not include the fine protocol granularity required to ensure network security inside an environment with weak protocols lacking authentication and encryption. By implementing a more specific and more intelligent packet inspection mechanism, tailored traffic flow analysis, and unique packet tampering detection, IDS technology developed specifically for SCADA environments can be deployed with confidence in detecting malicious activity.

  17. Intrusion detection: systems and models

    Science.gov (United States)

    Sherif, J. S.; Dearmond, T. G.

    2002-01-01

    This paper puts forward a review of state of the art and state of the applicability of intrusion detection systems, and models. The paper also presents a classfication of literature pertaining to intrusion detection.

  18. Intrusion Detection in NEAR System by Anti-denoising Traffic Data Series using Discrete Wavelet Transform

    Directory of Open Access Journals (Sweden)

    VANCEA, F.

    2014-11-01

    Full Text Available The paper presents two methods for detecting anomalies in data series derived from network traffic. Intrusion detection systems based on network traffic analysis are able to respond to incidents never seen before by detecting anomalies in data series extracted from the traffic. Some anomalies manifest themselves as pulses of various sizes and shapes, superimposed on series corresponding to normal traffic. In order to detect those impulses we propose two methods based on discrete wavelet transformation. Their effectiveness expressed in relative thresholds on pulse amplitude for no false negatives and no false positives is then evaluated against pulse duration and Hurst characteristic of original series. Different base functions are also evaluated for efficiency in the context of the proposed methods.

  19. Passive intrusion detection system

    Science.gov (United States)

    Laue, E. G. (Inventor)

    1980-01-01

    An intrusion detection system is described in which crystal oscillators are used to provide a frequency which varies as a function of fluctuations of a particular environmental property of the atmosphere, e.g., humidity, in the protected volume. The system is based on the discovery that the frequency of an oscillator whose crystal is humidity sensitive, varies at a frequency or rate which is within a known frequency band, due to the entry of an intruder into the protected volume. The variable frequency is converted into a voltage which is then filtered by a filtering arrangement which permits only voltage variations at frequencies within the known frequency band to activate an alarm, while inhibiting the alarm activation when the voltage frequency is below or above the known frequency band.

  20. Intrusion Detection System Based on Decision Tree over Big Data in Fog Environment

    Directory of Open Access Journals (Sweden)

    Kai Peng

    2018-01-01

    Full Text Available Fog computing, as the supplement of cloud computing, can provide low-latency services between mobile users and the cloud. However, fog devices may encounter security challenges as a result of the fog nodes being close to the end users and having limited computing ability. Traditional network attacks may destroy the system of fog nodes. Intrusion detection system (IDS is a proactive security protection technology and can be used in the fog environment. Although IDS in tradition network has been well investigated, unfortunately directly using them in the fog environment may be inappropriate. Fog nodes produce massive amounts of data at all times, and, thus, enabling an IDS system over big data in the fog environment is of paramount importance. In this study, we propose an IDS system based on decision tree. Firstly, we propose a preprocessing algorithm to digitize the strings in the given dataset and then normalize the whole data, to ensure the quality of the input data so as to improve the efficiency of detection. Secondly, we use decision tree method for our IDS system, and then we compare this method with Naïve Bayesian method as well as KNN method. Both the 10% dataset and the full dataset are tested. Our proposed method not only completely detects four kinds of attacks but also enables the detection of twenty-two kinds of attacks. The experimental results show that our IDS system is effective and precise. Above all, our IDS system can be used in fog computing environment over big data.

  1. Information Engineering and Adaptive Data Systems

    Science.gov (United States)

    King, T. A.; Walker, R. J.; Joy, S. P.; Roberts, D. A.; Thieman, J. R.

    2006-12-01

    Information engineering is a rigorous architectural approach to developing and deploying applications within an enterprise. It progresses through natural stages of analysis, design and implementation with the focus on how information is organized to achieve desired objectives. NASA has undertaken the task of organizing and leveraging the vast expanse of information in the Heliophysics domain. To achieve this goal NASA has supported the SPASE modeling effort and established domain specific Virtual Observatories. We explore how this effort fits into an information engineering approach and discuss the important and relevance of data modeling, standardization and open frameworks to achieving NASA's goals. The SPASE modeling effort and independent analysis by some of the Virtual Observatories have determined that the best solution is the development of data systems that are organized based on available resources, that is, adaptive to their environment. We explore why adaptive data systems are the best choice for reducing information entropy, adding value and improving information dissemination within NASA's Heliophysics domain.

  2. Adaptable data management for systems biology investigations

    Directory of Open Access Journals (Sweden)

    Burdick David

    2009-03-01

    Full Text Available Abstract Background Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. Results The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry. We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents. Conclusion Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community.

  3. Adaptable data management for systems biology investigations

    Science.gov (United States)

    Boyle, John; Rovira, Hector; Cavnor, Chris; Burdick, David; Killcoyne, Sarah; Shmulevich, Ilya

    2009-01-01

    Background Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. Results The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry). We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents. Conclusion Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community. PMID:19265554

  4. A Real-Time Intrusion Detection System using Data Mining Technique

    Directory of Open Access Journals (Sweden)

    Fang-Yie Leu

    2008-04-01

    Full Text Available Presently, most computers authenticate user ID and password before users can login these systems. However, danger soon comes if the two items are known to hackers. In this paper, we propose a system, named Intrusion Detection and Identification System (IDIS, which builds a profile for each user in an intranet to keep track his/her usage habits as forensic features with which IDIS can identify who the underlying user in the intranet is. Our experimental results show that the recognition accuracy of students of computer science department is up to 98.99%.

  5. Network Intrusion Detection System using Apache Storm

    Directory of Open Access Journals (Sweden)

    Muhammad Asif Manzoor

    2017-06-01

    Full Text Available Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various systems are proposed to enhance the network security. We are proposing to use anomaly based network intrusion detection system in this work. Anomaly based intrusion detection system can identify the new network threats. We also propose to use Real-time Big Data Stream Processing Framework, Apache Storm, for the implementation of network intrusion detection system. Apache Storm can help to manage the network traffic which is generated at enormous speed and size and the network traffic speed and size is constantly increasing. We have used Support Vector Machine in this work. We use Knowledge Discovery and Data Mining 1999 (KDD’99 dataset to test and evaluate our proposed solution.

  6. An automatically tuning intrusion detection system.

    Science.gov (United States)

    Yu, Zhenwei; Tsai, Jeffrey J P; Weigert, Thomas

    2007-04-01

    An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup'99 intrusion detection dataset. Experimental results show that the system achieves up to 35% improvement in terms of misclassification cost when compared with a system lacking the tuning feature. If only 10% false predictions are used to tune the model, the system still achieves about 30% improvement. Moreover, when tuning is not delayed too long, the system can achieve about 20% improvement, with only 1.3% of the false predictions used to tune the model. The results of the experiments show that a practical system can be built based on ATIDS: system operators can focus on verification of predictions with low confidence, as only those predictions determined to be false will be used to tune the detection model.

  7. Data-Adaptable Modeling and Optimization for Runtime Adaptable Systems

    Science.gov (United States)

    2016-06-08

    MONITOR’S REPORT NUMBER(S) 16. SECURITY CLASSIFICATION OF: 19b. TELEPHONE NUMBER (Include area code) The public reporting burden for this collection...often encounter situations in which it is unable to retrieve video or GPS data in remote areas . A data-adaptable approach should enable such an...Farrell, M. Okincha, M. Parmar, and B. Wandell, “Using visible SNR (vSNR) to compare the image quality of pixel binning and digital resizing ,” In Proc

  8. Seismic intrusion detector system

    Science.gov (United States)

    Hawk, Hervey L.; Hawley, James G.; Portlock, John M.; Scheibner, James E.

    1976-01-01

    A system for monitoring man-associated seismic movements within a control area including a geophone for generating an electrical signal in response to seismic movement, a bandpass amplifier and threshold detector for eliminating unwanted signals, pulse counting system for counting and storing the number of seismic movements within the area, and a monitoring system operable on command having a variable frequency oscillator generating an audio frequency signal proportional to the number of said seismic movements.

  9. Intrusion Detection Systems with Live Knowledge System

    Science.gov (United States)

    2016-05-31

    AFRL-AFOSR-JP-TR-2016-0058 Intrusion Detection Systems with Live Knowledge System Byeong Ho Kang UNIVERSITY OF TASMANIA Final Report 05/31/2016...COVERED (From - To) 20 May 2015 to 19 May 2016 4. TITLE AND SUBTITLE Intrusion Detection Systems with Live Knowledge System 5a.  CONTRACT NUMBER 5b...298 10/26/2016https://livelink.ebs.afrl.af.mil/livelink/llisapi.dll Final Report for AOARD Grant FA2386-15-1-4061 “ Intrusion Detection Systems with

  10. Research on IPv6 intrusion detection system Snort-based

    Science.gov (United States)

    Shen, Zihao; Wang, Hui

    2010-07-01

    This paper introduces the common intrusion detection technologies, discusses the work flow of Snort intrusion detection system, and analyzes IPv6 data packet encapsulation and protocol decoding technology. We propose the expanding Snort architecture to support IPv6 intrusion detection in accordance with CIDF standard combined with protocol analysis technology and pattern matching technology, and present its composition. The research indicates that the expanding Snort system can effectively detect various intrusion attacks; it is high in detection efficiency and detection accuracy and reduces false alarm and omission report, which effectively solves the problem of IPv6 intrusion detection.

  11. An artificial bioindicator system for network intrusion detection.

    Science.gov (United States)

    Blum, Christian; Lozano, José A; Davidson, Pedro Pinacho

    2015-01-01

    An artificial bioindicator system is developed in order to solve a network intrusion detection problem. The system, inspired by an ecological approach to biological immune systems, evolves a population of agents that learn to survive in their environment. An adaptation process allows the transformation of the agent population into a bioindicator that is capable of reacting to system anomalies. Two characteristics stand out in our proposal. On the one hand, it is able to discover new, previously unseen attacks, and on the other hand, contrary to most of the existing systems for network intrusion detection, it does not need any previous training. We experimentally compare our proposal with three state-of-the-art algorithms and show that it outperforms the competing approaches on widely used benchmark data.

  12. Smart sensor systems for outdoor intrusion detection

    International Nuclear Information System (INIS)

    Lynn, J.K.

    1988-01-01

    A major improvement in outdoor perimeter security system probability of detection (PD) and reduction in false alarm rate (FAR) and nuisance alarm rate (NAR) may be obtained by analyzing the indications immediately preceding an event which might be interpreted as an intrusion. Existing systems go into alarm after crossing a threshold. Very slow changes, which accumulate until the threshold is reached, may be assessed falsely as an intrusion. A hierarchial program has begun at Stellar to develop a modular, expandable Smart Sensor system which may be interfaced to most types of sensor and alarm reporting systems. A major upgrade to the SSI Test Site is in progress so that intrusions may be simulated in a controlled and repeatable manner. A test platform is being constructed which will operate in conduction with a mobile instrumentation center with CCTVB, lighting control, weather and data monitoring and remote control of the test platform and intrusion simulators. Additional testing was contracted with an independent test facility to assess the effects of severe winter weather conditions

  13. IMPLEMENTASI DAN ANALISA HASIL DATA MINING UNTUK KLASIFIKASI SERANGAN PADA INTRUSION DETECTION SYSTEM (IDS DENGAN ALGORITMA C4.5

    Directory of Open Access Journals (Sweden)

    Izza Khaerani

    2015-10-01

    Full Text Available Intrusion Detection System (IDS merupakan sebuah kemampuan yang dimiliki oleh sebuah sistem atau perangkat untuk dapat melakukan deteksi terhadap serangan yang mungkin terjadi dalam jaringan baik lokal maupun yang terhubung dengan internet. Masalah dimulai ketika paket data yang datang sangat banyak dan harus di analisa di kemudian hari. Teknik Data Mining merupakan teknik yang tepat untuk melakukan analisa terhadap sebuah data. Beberapa penelitian telah menggunakan teknik data mining untuk mengatasi masalah serangan IDS seperti analisis frequent itemset, analisis clustering, analisis klasifikasi dan analisis asosiasi. Tujuan dari penelitian ini adalah untuk mengklasifikasikan serangan pada data-data yang diujikan dengan menggunakan metode klasifikasi dan algoritma klasifikasi C4.5. Penelitian ini menggunakan koleksi data dari KDD’99 dan memiliki 41 atribut dimana atribut ini dilakukan fitur seleksi untuk menghapus atribut yang tidak relevan dengan menggunakan teknik evolusi. Hasil yang didapatkan dari fitur seleksi ini adalah 16 atribut dengan akurasi tinggi mencapai 98,67% dari 41 atribut yang ada. Kemudian hasilnya dilakukan pemodelan dengan menggunakan algoritma C4.5 dan menghasilkan sebuah aturan untuk digunakan dalam implementasi sistem analisa klasifikasi data. Aturan yang dihasilkan dapat digunakan dalam sistem untuk mengklasifikasikan data serangan seperti dos, u2r, r2l dan probe serta aktifitas jaringan normal. Kata Kunci: Klasifikasi, Algoritma C4.5, Fitur Seleksi, Evolusi, Intrution Detection System, IDS.

  14. Improving Intrusion Detection System Based on Snort Rules for Network Probe Attacks Detection with Association Rules Technique of Data Mining

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

    Full Text Available The intrusion detection system (IDS is an important network security tool for securing computer and network systems. It is able to detect and monitor network traffic data. Snort IDS is an open-source network security tool. It can search and match rules with network traffic data in order to detect attacks, and generate an alert. However, the Snort IDS  can detect only known attacks. Therefore, we have proposed a procedure for improving Snort IDS rules, based on the association rules data mining technique for detection of network probe attacks.  We employed the MIT-DARPA 1999 data set for the experimental evaluation. Since behavior pattern traffic data are both normal and abnormal, the abnormal behavior data is detected by way of the Snort IDS. The experimental results showed that the proposed Snort IDS rules, based on data mining detection of network probe attacks, proved more efficient than the original Snort IDS rules, as well as icmp.rules and icmp-info.rules of Snort IDS.  The suitable parameters for the proposed Snort IDS rules are defined as follows: Min_sup set to 10%, and Min_conf set to 100%, and through the application of eight variable attributes. As more suitable parameters are applied, higher accuracy is achieved.

  15. Abstracting audit data for lightweight intrusion detection

    KAUST Repository

    Wang, Wei

    2010-01-01

    High speed of processing massive audit data is crucial for an anomaly Intrusion Detection System (IDS) to achieve real-time performance during the detection. Abstracting audit data is a potential solution to improve the efficiency of data processing. In this work, we propose two strategies of data abstraction in order to build a lightweight detection model. The first strategy is exemplar extraction and the second is attribute abstraction. Two clustering algorithms, Affinity Propagation (AP) as well as traditional k-means, are employed to extract the exemplars, and Principal Component Analysis (PCA) is employed to abstract important attributes (a.k.a. features) from the audit data. Real HTTP traffic data collected in our institute as well as KDD 1999 data are used to validate the two strategies of data abstraction. The extensive test results show that the process of exemplar extraction significantly improves the detection efficiency and has a better detection performance than PCA in data abstraction. © 2010 Springer-Verlag.

  16. Apriori-based network intrusion detection system

    International Nuclear Information System (INIS)

    Wang Wenjin; Liu Junrong; Liu Baoxu

    2012-01-01

    With the development of network communication technology, more and more social activities run by Internet. In the meantime, the network information security is getting increasingly serious. Intrusion Detection System (IDS) has greatly improved the general security level of whole network. But there are still many problem exists in current IDS, e.g. high leak rate detection/false alarm rates and feature library need frequently upgrade. This paper presents an association-rule based IDS. This system can detect unknown attack by generate rules from training data. Experiment in last chapter proved the system has great accuracy on unknown attack detection. (authors)

  17. NIST Special Publication on Intrusion Detection Systems

    National Research Council Canada - National Science Library

    Bace, Rebecca Gurley

    2001-01-01

    Intrusion detection systems (IDSs) are software or hardware systems that automate the process of monitoring the events occurring in a computer system or network, analyzing them for signs of security problems...

  18. Perimeter intrusion detection and assessment system

    Energy Technology Data Exchange (ETDEWEB)

    Eaton, M.J.; Jacobs, J.; McGovern, D.E.

    1977-01-01

    The key elements of the system considered at a materials storage site are intrusion sensors, alarm assessment, and system control and display. Three papers discussing each of these topics are compiled. They are abstracted individually. (JSR)

  19. Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

    Science.gov (United States)

    Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

    In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

  20. A Fusion of Multiagent Functionalities for Effective Intrusion Detection System

    OpenAIRE

    Krishnan Sadhasivan, Dhanalakshmi; Balasubramanian, Kannapiran

    2017-01-01

    Provision of high security is one of the active research areas in the network applications. The failure in the centralized system based on the attacks provides less protection. Besides, the lack of update of new attacks arrival leads to the minimum accuracy of detection. The major focus of this paper is to improve the detection performance through the adaptive update of attacking information to the database. We propose an Adaptive Rule-Based Multiagent Intrusion Detection System (ARMA-IDS) to...

  1. Intrusion Detection in Control Systems using Sequence Characteristics

    Science.gov (United States)

    Kiuchi, Mai; Onoda, Takashi

    Intrusion detection is considered effective in control systems. Sequences of the control application behavior observed in the communication, such as the order of the control device to be controlled, are important in control systems. However, most intrusion detection systems do not effectively reflect sequences in the application layer into the detection rules. In our previous work, we considered utilizing sequences for intrusion detection in control systems, and demonstrated the usefulness of sequences for intrusion detection. However, manually writing the detection rules for a large system can be difficult, so using machine learning methods becomes feasible. Also, in the case of control systems, there have been very few observed cyber attacks, so we have very little knowledge of the attack data that should be used to train the intrusion detection system. In this paper, we use an approach that combines CRF (Conditional Random Field) considering the sequence of the system, thus able to reflect the characteristics of control system sequences into the intrusion detection system, and also does not need the knowledge of attack data to construct the detection rules.

  2. Security Enrichment in Intrusion Detection System Using Classifier Ensemble

    Directory of Open Access Journals (Sweden)

    Uma R. Salunkhe

    2017-01-01

    Full Text Available In the era of Internet and with increasing number of people as its end users, a large number of attack categories are introduced daily. Hence, effective detection of various attacks with the help of Intrusion Detection Systems is an emerging trend in research these days. Existing studies show effectiveness of machine learning approaches in handling Intrusion Detection Systems. In this work, we aim to enhance detection rate of Intrusion Detection System by using machine learning technique. We propose a novel classifier ensemble based IDS that is constructed using hybrid approach which combines data level and feature level approach. Classifier ensembles combine the opinions of different experts and improve the intrusion detection rate. Experimental results show the improved detection rates of our system compared to reference technique.

  3. Simulating spatial adaption of groundwater pumping on seawater intrusion in coastal regions

    Science.gov (United States)

    Grundmann, Jens; Ladwig, Robert; Schütze, Niels; Walther, Marc

    2016-04-01

    Coastal aquifer systems are used intensively to meet the growing demands for water in those regions. They are especially at risk for the intrusion of seawater due to aquifer overpumping, limited groundwater replenishment and unsustainable groundwater management which in turn also impacts the social and economical development of coastal regions. One example is the Al-Batinah coastal plain in northern Oman where irrigated agriculture is practiced by lots of small scaled farms in different distances from the sea, each of them pumping their water from coastal aquifer. Due to continuous overpumping and progressing saltwater intrusion farms near the coast had to close since water for irrigation got too saline. For investigating appropriate management options numerical density dependent groundwater modelling is required which should also portray the adaption of groundwater abstraction schemes on the water quality. For addressing this challenge a moving inner boundary condition is implemented in the numerical density dependent groundwater model which adjusts the locations for groundwater abstraction according to the position of the seawater intrusion front controlled by thresholds of relative chloride concentration. The adaption process is repeated for each management cycle within transient model simulations and allows for considering feedbacks with the consumers e.g. the agriculture by moving agricultural farms more inland or towards the sea if more fertile soils at the coast could be recovered. For finding optimal water management strategies efficiently, the behaviour of the numerical groundwater model for different extraction and replenishment scenarios is approximated by an artificial neural network using a novel approach for state space surrogate model development. Afterwards the derived surrogate is coupled with an agriculture module within a simulation based water management optimisation framework to achieve optimal cropping pattern and water abstraction schemes

  4. Intrusion Detection amp Prevention Systems - Sourcefire Snort

    Directory of Open Access Journals (Sweden)

    Rajesh Vuppala

    2015-08-01

    Full Text Available Information security is a challenging issue for all business organizations today amidst increasing cyber threats. While there are many alternative intrusion detection amp prevention systems available to choose from selecting the best solution to implement to detect amp prevent cyber-attacks is a difficult task. The best solution is of the one that gets the best reviews and suits the organizations needs amp budget. In this review paper we summarize various classes of intrusion detection and prevention systems compare features of alternative solutions and make recommendation for implementation of one as the best solution for business organization in Fiji.

  5. Data Mining Usage in Corporate Information Security: Intrusion Detection Applications

    Directory of Open Access Journals (Sweden)

    Al Quhtani Masoud

    2017-03-01

    Full Text Available Background: The globalization era has brought with it the development of high technology, and therefore new methods of preserving and storing data. New data storing techniques ensure data are stored for longer periods of time, more efficiently and with a higher quality, but also with a higher data abuse risk. Objective: The goal of the paper is to provide a review of the data mining applications for the purpose of corporate information security, and intrusion detection in particular. Methods/approach: The review was conducted using the systematic analysis of the previously published papers on the usage of data mining in the field of corporate information security. Results: This paper demonstrates that the use of data mining applications is extremely useful and has a great importance for establishing corporate information security. Data mining applications are directly related to issues of intrusion detection and privacy protection. Conclusions: The most important fact that can be specified based on this study is that corporations can establish a sustainable and efficient data mining system that will ensure privacy and successful protection against unwanted intrusions.

  6. Poseidon: A 2-tier Anomaly-based Intrusion Detection System

    NARCIS (Netherlands)

    Bolzoni, D.; Zambon, Emmanuele; Etalle, Sandro; Hartel, Pieter H.

    2005-01-01

    We present Poseidon, a new anomaly based intrusion detection system. Poseidon is payload-based, and presents a two-tier architecture: the first stage consists of a Self-Organizing Map, while the second one is a modified PAYL system. Our benchmarks on the 1999 DARPA data set show a higher detection

  7. Distributed fiber optic moisture intrusion sensing system

    Science.gov (United States)

    Weiss, Jonathan D.

    2003-06-24

    Method and system for monitoring and identifying moisture intrusion in soil such as is contained in landfills housing radioactive and/or hazardous waste. The invention utilizes the principle that moist or wet soil has a higher thermal conductance than dry soil. The invention employs optical time delay reflectometry in connection with a distributed temperature sensing system together with heating means in order to identify discrete areas within a volume of soil wherein temperature is lower. According to the invention an optical element and, optionally, a heating element may be included in a cable or other similar structure and arranged in a serpentine fashion within a volume of soil to achieve efficient temperature detection across a large area or three dimensional volume of soil. Remediation, moisture countermeasures, or other responsive action may then be coordinated based on the assumption that cooler regions within a soil volume may signal moisture intrusion where those regions are located.

  8. In-situ trainable intrusion detection system

    Energy Technology Data Exchange (ETDEWEB)

    Symons, Christopher T.; Beaver, Justin M.; Gillen, Rob; Potok, Thomas E.

    2016-11-15

    A computer implemented method detects intrusions using a computer by analyzing network traffic. The method includes a semi-supervised learning module connected to a network node. The learning module uses labeled and unlabeled data to train a semi-supervised machine learning sensor. The method records events that include a feature set made up of unauthorized intrusions and benign computer requests. The method identifies at least some of the benign computer requests that occur during the recording of the events while treating the remainder of the data as unlabeled. The method trains the semi-supervised learning module at the network node in-situ, such that the semi-supervised learning modules may identify malicious traffic without relying on specific rules, signatures, or anomaly detection.

  9. Perimeter intrusion detection and assessment system

    Energy Technology Data Exchange (ETDEWEB)

    Eaton, M.J.; Jacobs, J.; McGovern, D.E.

    1977-11-01

    To obtain an effective perimeter intrusion detection system requires careful sensor selection, procurement, and installation. The selection process involves a thorough understanding of the unique site features and how these features affect the performance of each type of sensor. It is necessary to develop procurement specifications to establish acceptable sensor performance limits. Careful explanation and inspection of critical installation dimensions is required during on-site construction. The implementation of these activities at a particular site is discussed.

  10. Perimeter intrusion detection and assessment system

    International Nuclear Information System (INIS)

    Eaton, M.J.; Jacobs, J.; McGovern, D.E.

    1977-11-01

    To obtain an effective perimeter intrusion detection system requires careful sensor selection, procurement, and installation. The selection process involves a thorough understanding of the unique site features and how these features affect the performance of each type of sensor. It is necessary to develop procurement specifications to establish acceptable sensor performance limits. Careful explanation and inspection of critical installation dimensions is required during on-site construction. The implementation of these activities at a particular site is discussed

  11. A Fusion of Multiagent Functionalities for Effective Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Dhanalakshmi Krishnan Sadhasivan

    2017-01-01

    Full Text Available Provision of high security is one of the active research areas in the network applications. The failure in the centralized system based on the attacks provides less protection. Besides, the lack of update of new attacks arrival leads to the minimum accuracy of detection. The major focus of this paper is to improve the detection performance through the adaptive update of attacking information to the database. We propose an Adaptive Rule-Based Multiagent Intrusion Detection System (ARMA-IDS to detect the anomalies in the real-time datasets such as KDD and SCADA. Besides, the feedback loop provides the necessary update of attacks in the database that leads to the improvement in the detection accuracy. The combination of the rules and responsibilities for multiagents effectively detects the anomaly behavior, misuse of response, or relay reports of gas/water pipeline data in KDD and SCADA, respectively. The comparative analysis of the proposed ARMA-IDS with the various existing path mining methods, namely, random forest, JRip, a combination of AdaBoost/JRip, and common path mining on the SCADA dataset conveys that the effectiveness of the proposed ARMA-IDS in the real-time fault monitoring. Moreover, the proposed ARMA-IDS offers the higher detection rate in the SCADA and KDD cup 1999 datasets.

  12. Data mining approach to web application intrusions detection

    Science.gov (United States)

    Kalicki, Arkadiusz

    2011-10-01

    Web applications became most popular medium in the Internet. Popularity, easiness of web application script languages and frameworks together with careless development results in high number of web application vulnerabilities and high number of attacks performed. There are several types of attacks possible because of improper input validation: SQL injection Cross-site scripting, Cross-Site Request Forgery (CSRF), web spam in blogs and others. In order to secure web applications intrusion detection (IDS) and intrusion prevention systems (IPS) are being used. Intrusion detection systems are divided in two groups: misuse detection (traditional IDS) and anomaly detection. This paper presents data mining based algorithm for anomaly detection. The principle of this method is the comparison of the incoming HTTP traffic with a previously built profile that contains a representation of the "normal" or expected web application usage sequence patterns. The frequent sequence patterns are found with GSP algorithm. Previously presented detection method was rewritten and improved. Some tests show that the software catches malicious requests, especially long attack sequences, results quite good with medium length sequences, for short length sequences must be complemented with other methods.

  13. Water System Adaptation To Hydrological Changes: Module 6, Synchronous Management of Storm Surge, Sea Level Rise, and Salt Water Intrusion: Case Study in Mattapoisett, Massachusetts, U.S.A.

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  14. Non-intrusive Quality Analysis of Monitoring Data

    CERN Document Server

    Brightwell, M; Suwalska, Anna

    2010-01-01

    Any large-scale operational system running over a variety of devices requires a monitoring mechanism to assess the health of the overall system. The Technical Infrastructure Monitoring System (TIM) at CERN is one such system, and monitors a wide variety of devices and their properties, such as electricity supplies, device temperatures, liquid flows etc. Without adequate quality assurance, the data collected from such devices leads to false-positives and false-negatives, reducing the effectiveness of the monitoring system. The quality must, however, be measured in a non-intrusive way, so that the critical path of the data flow is not affected by the quality computation. The quality computation should also scale to large volumes of incoming data. To address these challenges, we develop a new statistical module, which monitors the data collected by TIM and reports its quality to the operators. The statistical module uses Oracle RDBMS as the underlying store, and builds hierarchical summaries on the basic events ...

  15. A Targeted Attack For Enhancing Resiliency of Intelligent Intrusion Detection Modules in Energy Cyber Physical Systems

    Energy Technology Data Exchange (ETDEWEB)

    Youssef, Tarek [Florida Intl Univ., Miami, FL (United States); El Hariri, Mohammad [Florida Intl Univ., Miami, FL (United States); Habib, Hani [Florida Intl Univ., Miami, FL (United States); Mohammed, Osama [Florida Intl Univ., Miami, FL (United States); Harmon, E [Florida Intl Univ., Miami, FL (United States)

    2017-02-28

    Abstract— Secure high-speed communication is required to ensure proper operation of complex power grid systems and prevent malicious tampering activities. In this paper, artificial neural networks with temporal dependency are introduced for false data identification and mitigation for broadcasted IEC 61850 SMV messages. The fast responses of such intelligent modules in intrusion detection make them suitable for time- critical applications, such as protection. However, care must be taken in selecting the appropriate intelligence model and decision criteria. As such, this paper presents a customizable malware script to sniff and manipulate SMV messages and demonstrates the ability of the malware to trigger false positives in the neural network’s response. The malware developed is intended to be as a vaccine to harden the intrusion detection system against data manipulation attacks by enhancing the neural network’s ability to learn and adapt to these attacks.

  16. Windows Based Data Sets for Evaluation of Robustness of Host Based Intrusion Detection Systems (IDS to Zero-Day and Stealth Attacks

    Directory of Open Access Journals (Sweden)

    Waqas Haider

    2016-07-01

    Full Text Available The Windows Operating System (OS is the most popular desktop OS in the world, as it has the majority market share of both servers and personal computing necessities. However, as its default signature-based security measures are ineffectual for detecting zero-day and stealth attacks, it needs an intelligent Host-based Intrusion Detection System (HIDS. Unfortunately, a comprehensive data set that reflects the modern Windows OS’s normal and attack surfaces is not publicly available. To fill this gap, in this paper two open data sets generated by the cyber security department of the Australian Defence Force Academy (ADFA are introduced, namely: Australian Defence Force Academy Windows Data Set (ADFA-WD; and Australian Defence Force Academy Windows Data Set with a Stealth Attacks Addendum (ADFA-WD: SAA. Statistical analysis results based on these data sets show that, due to the low foot prints of modern attacks and high similarity of normal and attacked data, both these data sets are complex, and highly intelligent Host based Anomaly Detection Systems (HADS design will be required.

  17. Hybrid Intrusion Forecasting Framework for Early Warning System

    Science.gov (United States)

    Kim, Sehun; Shin, Seong-Jun; Kim, Hyunwoo; Kwon, Ki Hoon; Han, Younggoo

    Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

  18. The use of data-mining techniques for developing effective decisionsupport systems: A case study of simulating the effects ofclimate change on coastal salinity intrusion

    Science.gov (United States)

    Conrads, Paul; Edwin Roehl, Jr.

    2017-01-01

    Natural-resource managers and stakeholders face difficult challenges when managing interactions between natural and societal systems. Potential changes in climate could alter interactions between environmental and societal systems and adversely affect the availability of water resources in many coastal communities. The availability of freshwater in coastal streams can be threatened by saltwater intrusion. Even though the collective interests and computer skills of the community of managers, scientists and other stakeholders are quite varied, there is an overarching need for equal access by all to the scientific knowledge needed to make the best possible decisions. This paper describes a decision support system, PRISM-2, developed to evaluate salinity intrusion due to potential climate change along the South Carolina coast in southeastern USA. The decision support system is disseminated as a spreadsheet application and integrates the output of global circulation models, watershed models and salinity intrusion models with real-time databases for simulation, graphical user interfaces, and streaming displays of results. The results from PRISM-2 showed that a 31-cm and 62-cm increase in sea level reduced the daily availability of freshwater supply to a coastal municipal intake by 4% and 12% of the time, respectively. Future climate change projections by a global circulation model showed a seasonal change in salinity intrusion events from the summer to the fall for the majority of events.

  19. An intrusion detection system based on fiber hydrophone

    Science.gov (United States)

    Liu, Junrong; Qiu, Xiufen; Shen, Heping

    2017-10-01

    This paper provides a new intrusion detection system based on fiber hydrophone, focusing beam forming figure positioning according to the near field and high precision sound source location algorithm which can accurately position the intrusion; obtaining its behavior path , obtaining the intrusion events related information such as speed form tracking intrusion trace; And analyze identification the detected intrusion behavior. If the monitor area is larger, the algorithm will take too much time once, and influence the system response time, for reduce the calculating time. This paper provides way that coarse location first, and then scanned for accuracy, so as to realize the intrusion events (such as car, etc.) the remote monitoring of positioning. The system makes up the blank in process capture of the fiber optic intrusion detection technology, and improves the understanding of the invasion. Through the capture of the process of intrusion behavior, and the fusion detection of intrusion behavior itself, thus analysis, judgment, identification of the intrusion information can greatly reduce the rate of false positives, greatly improved the reliability and practicability of the perimeter security system.

  20. RePIDS: a multi tier real-time payload-based intrusion detection system

    NARCIS (Netherlands)

    Jamdagni, Aruna; Tan, Zhiyuan; Nanda, Priyadarsi; He, Xiangjian; Liu, Ren Ping

    2013-01-01

    Intrusion Detection System (IDS) deals with huge amount of network traffic and uses large feature set to discriminate normal pattern and intrusive pattern. However, most of existing systems lack the ability to process data for real-time anomaly detection. In this paper, we propose a 3-Tier Iterative

  1. Introduction To Intrusion Detection System Review

    Directory of Open Access Journals (Sweden)

    Rajni Tewatia

    2015-05-01

    Full Text Available Abstract Security of a network is always an important issue. With the continuously growing network the basic security such as firewall virus scanner is easily deceived by modern attackers who are experts in using software vulnerabilities to achieve their goals. For preventing such attacks we need even smarter security mechanism which act proactively and intelligently. Intrusion Detection System is the solution of such requirement. Many techniques have been used to implement IDS. These technique basically used in the detector part of IDS such as Neural Network Clustering Pattern Matching Rule Based Fuzzy Logic Genetic Algorithms and many more. To improve the performance of an IDS these approaches may be used in combination to build a hybrid IDS so that benefits of two o more approaches may be combined.

  2. A new physical barrier system for seawater intrusion control

    Science.gov (United States)

    Abdoulhalik, Antoifi; Ahmed, Ashraf; Hamill, G. A.

    2017-06-01

    The construction of subsurface physical barriers is one of various methods used to control seawater intrusion (SWI) in coastal aquifers. This study proposes the mixed physical barrier (MPB) as a new barrier system for seawater intrusion control, which combines an impermeable cutoff wall and a semi-permeable subsurface dam. The effect of the traditionally-used physical barriers on transient saltwater wedge dynamics was first explored for various hydraulic gradients, and the workability of the MPB was thereafter thoroughly analysed. A newly developed automated image analysis based on light-concentration conversion was used in the experiments, which were completed in a porous media tank. The numerical code SEAWAT was used to assess the consistency of the experimental data and examine the sensitivity of the performance of the barriers to various key parameters. The results show that the MPB induced a visible lifting of the dense saline flux upward towards the outlet by the light freshwater. This saltwater lifting mechanism, observed for the first time, induced significant reduction to the saline water intrusion length. The use of the MPB yielded up to 62% and 42% more reduction of the saltwater intrusion length than the semi-permeable dam and the cutoff wall, respectively. The performance achieved by the MPB with a wall depth of 40% of the aquifer thickness was greater than that of a single cutoff wall with a penetration depth of 90% of the aquifer thickness (about 13% extra reduction). This means that the MPB could produce better seawater intrusion reduction than the traditionally used barriers at even lower cost.

  3. Anomaly-based intrusion detection for SCADA systems

    International Nuclear Information System (INIS)

    Yang, D.; Usynin, A.; Hines, J. W.

    2006-01-01

    Most critical infrastructure such as chemical processing plants, electrical generation and distribution networks, and gas distribution is monitored and controlled by Supervisory Control and Data Acquisition Systems (SCADA. These systems have been the focus of increased security and there are concerns that they could be the target of international terrorists. With the constantly growing number of internet related computer attacks, there is evidence that our critical infrastructure may also be vulnerable. Researchers estimate that malicious online actions may cause $75 billion at 2007. One of the interesting countermeasures for enhancing information system security is called intrusion detection. This paper will briefly discuss the history of research in intrusion detection techniques and introduce the two basic detection approaches: signature detection and anomaly detection. Finally, it presents the application of techniques developed for monitoring critical process systems, such as nuclear power plants, to anomaly intrusion detection. The method uses an auto-associative kernel regression (AAKR) model coupled with the statistical probability ratio test (SPRT) and applied to a simulated SCADA system. The results show that these methods can be generally used to detect a variety of common attacks. (authors)

  4. Specification Mining for Intrusion Detection in Networked Control Systems

    NARCIS (Netherlands)

    Caselli, M.; Zambon, Emmanuele; Amann, Johanna; Sommer, Robin; Kargl, Frank

    2016-01-01

    This paper discusses a novel approach to specification-based intrusion detection in the field of networked control systems. Our approach reduces the substantial human effort required to deploy a specification-based intrusion detection system by automating the development of its specification rules.

  5. An adaptive semantic based mediation system for data interoperability among Health Information Systems.

    Science.gov (United States)

    Khan, Wajahat Ali; Khattak, Asad Masood; Hussain, Maqbool; Amin, Muhammad Bilal; Afzal, Muhammad; Nugent, Christopher; Lee, Sungyoung

    2014-08-01

    Heterogeneity in the management of the complex medical data, obstructs the attainment of data level interoperability among Health Information Systems (HIS). This diversity is dependent on the compliance of HISs with different healthcare standards. Its solution demands a mediation system for the accurate interpretation of data in different heterogeneous formats for achieving data interoperability. We propose an adaptive AdapteR Interoperability ENgine mediation system called ARIEN, that arbitrates between HISs compliant to different healthcare standards for accurate and seamless information exchange to achieve data interoperability. ARIEN stores the semantic mapping information between different standards in the Mediation Bridge Ontology (MBO) using ontology matching techniques. These mappings are provided by our System for Parallel Heterogeneity (SPHeRe) matching system and Personalized-Detailed Clinical Model (P-DCM) approach to guarantee accuracy of mappings. The realization of the effectiveness of the mappings stored in the MBO is evaluation of the accuracy in transformation process among different standard formats. We evaluated our proposed system with the transformation process of medical records between Clinical Document Architecture (CDA) and Virtual Medical Record (vMR) standards. The transformation process achieved over 90 % of accuracy level in conversion process between CDA and vMR standards using pattern oriented approach from the MBO. The proposed mediation system improves the overall communication process between HISs. It provides an accurate and seamless medical information exchange to ensure data interoperability and timely healthcare services to patients.

  6. Intrusion detection systems: complement to firewall security system ...

    African Journals Online (AJOL)

    Intrusion detection systems: complement to firewall security system. ... Information Impact: Journal of Information and Knowledge Management. Journal Home ... If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

  7. Effects of igneous intrusions on the petroleum system: a review

    NARCIS (Netherlands)

    Senger, Kim; Millett, John; Planke, Sverre; Ogata, Kei; Eide, Christian Haug; Festøy, Marte; Galland, Olivier; Jerram, Dougal A.

    2017-01-01

    Igneous intrusions feature in many sedimentary basins where hydrocarbon exploration and production is continuing. Owing to distinct geophysical property contrasts with siliciclastic host rocks (e.g., higher Vp, density and resistivity than host rocks), intrusions can be easily delineated within data

  8. A Retroactive-Burst Framework for Automated Intrusion Response System

    Directory of Open Access Journals (Sweden)

    Alireza Shameli-Sendi

    2013-01-01

    Full Text Available The aim of this paper is to present an adaptive and cost-sensitive model to prevent security intrusions. In most automated intrusion response systems, response selection is performed locally based on current threat without using the knowledge of attacks history. Another challenge is that a group of responses are applied without any feedback mechanism to measure the response effect. We address these problems through retroactive-burst execution of responses and a Response Coordinator (RC mechanism, the main contributions of this work. The retroactive-burst execution consists of several burst executions of responses with, at the end of each burst, a mechanism for measuring the effectiveness of the applied responses by the risk assessment component. The appropriate combination of responses must be considered for each burst execution to mitigate the progress of the attack without necessarily running the next round of responses, because of the impact on legitimate users. In the proposed model, there is a multilevel response mechanism. To indicate which level is appropriate to apply based on the retroactive-burst execution, we get help from a Response Coordinator mechanism. The applied responses can improve the health of Applications, Kernel, Local Services, Network Services, and Physical Status. Based on these indexes, the RC gives a general overview of an attacker’s goal in a distributed environment.

  9. A Labeled Data Set For Flow-based Intrusion Detection

    NARCIS (Netherlands)

    Sperotto, Anna; Sadre, R.; van Vliet, Frank; Pras, Aiko; Nunzi, Giorgio; Scoglio, Caterina; Li, Xing

    2009-01-01

    Flow-based intrusion detection has recently become a promising security mechanism in high speed networks (1-10 Gbps). Despite the richness in contributions in this field, benchmarking of flow-based IDS is still an open issue. In this paper, we propose the first publicly available, labeled data set

  10. Ensemble of classifiers based network intrusion detection system performance bound

    CSIR Research Space (South Africa)

    Mkuzangwe, Nenekazi NP

    2017-11-01

    Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

  11. Novel Non-Intrusive Vibration Monitoring System for Turbopumps Project

    Data.gov (United States)

    National Aeronautics and Space Administration — ASRI proposes to develop an advanced and commercially viable Non-Intrusive Vibration Monitoring System (NI-VMS) which can provide effective on-line/off-line engine...

  12. Implementing an Intrusion Detection System in the Mysea Architecture

    National Research Council Canada - National Science Library

    Tenhunen, Thomas

    2008-01-01

    .... The objective of this thesis is to design an intrusion detection system (IDS) architecture that permits administrators operating on MYSEA client machines to conveniently view and analyze IDS alerts from the single level networks...

  13. Abstracting massive data for lightweight intrusion detection in computer networks

    KAUST Repository

    Wang, Wei

    2016-10-15

    Anomaly intrusion detection in big data environments calls for lightweight models that are able to achieve real-time performance during detection. Abstracting audit data provides a solution to improve the efficiency of data processing in intrusion detection. Data abstraction refers to abstract or extract the most relevant information from the massive dataset. In this work, we propose three strategies of data abstraction, namely, exemplar extraction, attribute selection and attribute abstraction. We first propose an effective method called exemplar extraction to extract representative subsets from the original massive data prior to building the detection models. Two clustering algorithms, Affinity Propagation (AP) and traditional . k-means, are employed to find the exemplars from the audit data. . k-Nearest Neighbor (k-NN), Principal Component Analysis (PCA) and one-class Support Vector Machine (SVM) are used for the detection. We then employ another two strategies, attribute selection and attribute extraction, to abstract audit data for anomaly intrusion detection. Two http streams collected from a real computing environment as well as the KDD\\'99 benchmark data set are used to validate these three strategies of data abstraction. The comprehensive experimental results show that while all the three strategies improve the detection efficiency, the AP-based exemplar extraction achieves the best performance of data abstraction.

  14. Network Intrusion Detection System – A Novel Approach

    Directory of Open Access Journals (Sweden)

    Krish Pillai

    2013-08-01

    Full Text Available Network intrusion starts off with a series of unsuccessful breakin attempts and results eventually with the permanent or transient failure of an authentication or authorization system. Due to the current complexity of authentication systems, clandestine attempts at intrusion generally take considerable time before the system gets compromised or damaging change is affected to the system giving administrators a window of opportunity to proactively detect and prevent intrusion. Therefore maintaining a high level of sensitivity to abnormal access patterns is a very effective way of preventing possible break-ins. Under normal circumstances, gross errors on the part of the user can cause authentication and authorization failures on all systems. A normal distribution of failed attempts should be tolerated while abnormal attempts should be recognized as such and flagged. But one cannot manage what one cannot measure. This paper proposes a method that can efficiently quantify the behaviour of users on a network so that transient changes in usage can be detected, categorized based on severity, and closely investigated for possible intrusion. The author proposes the identification of patterns in protocol usage within a network to categorize it for surveillance. Statistical anomaly detection, under which category this approach falls, generally uses simple statistical tests such as mean and standard deviation to detect behavioural changes. The author proposes a novel approach using spectral density as opposed to using time domain data, allowing a clear separation or access patterns based on periodicity. Once a spectral profile has been identified for network, deviations from this profile can be used as an indication of a destabilized or compromised network. Spectral analysis of access patterns is done using the Fast Fourier Transform (FFT, which can be computed in Θ(N log N operations. The paper justifies the use of this approach and presents preliminary

  15. The design about the intrusion defense system for IHEP

    International Nuclear Information System (INIS)

    Liu Baoxu; Xu Rongsheng; Yu Chuansong; Wu Chunzhen

    2003-01-01

    With the development of network technologies, limitations on traditional methods of network security protection are becoming more and more obvious. An individual network security product or the simple combination of several products can hardly complete the goal of keeping from hackers' intrusion. Therefore, on the basis of the analyses about the security problems of IHEPNET which is an open and scientific research network, the author designs an intrusion defense system especially for IHEPNET

  16. Intrusive versus domiciliated triatomines and the challenge of adapting vector control practices against Chagas disease

    Directory of Open Access Journals (Sweden)

    Etienne Waleckx

    2015-05-01

    Full Text Available Chagas disease prevention remains mostly based on triatomine vector control to reduce or eliminate house infestation with these bugs. The level of adaptation of triatomines to human housing is a key part of vector competence and needs to be precisely evaluated to allow for the design of effective vector control strategies. In this review, we examine how the domiciliation/intrusion level of different triatomine species/populations has been defined and measured and discuss how these concepts may be improved for a better understanding of their ecology and evolution, as well as for the design of more effective control strategies against a large variety of triatomine species. We suggest that a major limitation of current criteria for classifying triatomines into sylvatic, intrusive, domiciliary and domestic species is that these are essentially qualitative and do not rely on quantitative variables measuring population sustainability and fitness in their different habitats. However, such assessments may be derived from further analysis and modelling of field data. Such approaches can shed new light on the domiciliation process of triatomines and may represent a key tool for decision-making and the design of vector control interventions.

  17. Intrusive versus domiciliated triatomines and the challenge of adapting vector control practices against Chagas disease.

    Science.gov (United States)

    Waleckx, Etienne; Gourbière, Sébastien; Dumonteil, Eric

    2015-05-01

    Chagas disease prevention remains mostly based on triatomine vector control to reduce or eliminate house infestation with these bugs. The level of adaptation of triatomines to human housing is a key part of vector competence and needs to be precisely evaluated to allow for the design of effective vector control strategies. In this review, we examine how the domiciliation/intrusion level of different triatomine species/populations has been defined and measured and discuss how these concepts may be improved for a better understanding of their ecology and evolution, as well as for the design of more effective control strategies against a large variety of triatomine species. We suggest that a major limitation of current criteria for classifying triatomines into sylvatic, intrusive, domiciliary and domestic species is that these are essentially qualitative and do not rely on quantitative variables measuring population sustainability and fitness in their different habitats. However, such assessments may be derived from further analysis and modelling of field data. Such approaches can shed new light on the domiciliation process of triatomines and may represent a key tool for decision-making and the design of vector control interventions.

  18. Intrusive versus domiciliated triatomines and the challenge of adapting vector control practices against Chagas disease

    Science.gov (United States)

    Waleckx, Etienne; Gourbière, Sébastien; Dumonteil, Eric

    2015-01-01

    Chagas disease prevention remains mostly based on triatomine vector control to reduce or eliminate house infestation with these bugs. The level of adaptation of triatomines to human housing is a key part of vector competence and needs to be precisely evaluated to allow for the design of effective vector control strategies. In this review, we examine how the domiciliation/intrusion level of different triatomine species/populations has been defined and measured and discuss how these concepts may be improved for a better understanding of their ecology and evolution, as well as for the design of more effective control strategies against a large variety of triatomine species. We suggest that a major limitation of current criteria for classifying triatomines into sylvatic, intrusive, domiciliary and domestic species is that these are essentially qualitative and do not rely on quantitative variables measuring population sustainability and fitness in their different habitats. However, such assessments may be derived from further analysis and modelling of field data. Such approaches can shed new light on the domiciliation process of triatomines and may represent a key tool for decision-making and the design of vector control interventions. PMID:25993504

  19. Distributed reinforcement learning for adaptive and robust network intrusion response

    Science.gov (United States)

    Malialis, Kleanthis; Devlin, Sam; Kudenko, Daniel

    2015-07-01

    Distributed denial of service (DDoS) attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to defend against DDoS attacks where multiple reinforcement learning agents are installed on a set of routers and learn to rate-limit or throttle traffic towards a victim server. The focus of this paper is on online learning and scalability. We propose an approach that incorporates task decomposition, team rewards and a form of reward shaping called difference rewards. One of the novel characteristics of the proposed system is that it provides a decentralised coordinated response to the DDoS problem, thus being resilient to DDoS attacks themselves. The proposed system learns remarkably fast, thus being suitable for online learning. Furthermore, its scalability is successfully demonstrated in experiments involving 1000 learning agents. We compare our approach against a baseline and a popular state-of-the-art throttling technique from the network security literature and show that the proposed approach is more effective, adaptive to sophisticated attack rate dynamics and robust to agent failures.

  20. Hybrid feature selection for supporting lightweight intrusion detection systems

    Science.gov (United States)

    Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

    2017-08-01

    Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

  1. A modeling study of saltwater intrusion in the Andarax delta area using multiple data sources

    DEFF Research Database (Denmark)

    Antonsson, Arni Valur; Engesgaard, Peter Knudegaard; Jorreto, Sara

    context. The validity of a conceptual model is determined by different factors, where both data quantity and quality is of crucial importance. Often, when dealing with saltwater intrusion, data is limited. Therefore, using different sources (and types) of data can be beneficial and increase...... the understanding of the investigated system. A density dependent saltwater intrusion model has been established for the coastal zone of the Andarax aquifer, SE Spain, with the aim of obtaining a coherent (conceptual) understanding of the area. Recently drilled deep boreholes in  the Andarax delta revealed a far...... reaching saltwater intrusion in the area. Furthermore, the geological information obtained from these boreholes laid a foundation for a new hydrogeological conceptual model of the area, which we aim to assess in this simulation study.Appraisal of the conceptual model of the Andarax delta area is conducted...

  2. Intrusion problematic during water supply systems' operation

    Energy Technology Data Exchange (ETDEWEB)

    Mora-Rodriguez, Jesus; Lopez-Jimenez, P. Amparo [Departamento de Ingenieria Hidraulica y Medio Ambiente, Universidad Politecnica de Valencia, Camino de Vera, s/n, 46022, Valencia (Spain); Ramos, Helena M. [Civil Engineering Department and CEHIDRO, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal)

    2011-07-01

    Intrusion through leaks occurrence is a phenomenon when external fluid comes into water pipe systems. This phenomenon can cause contamination problems in drinking pipe systems. Hence, this paper focuses on the entry of external fluids across small leaks during normal operation conditions. This situation is especially important in elevated points of the pipe profile. Pressure variations can origin water volume losses and intrusion of contaminants into the drinking water pipes. This work focuses in obtaining up the physical representation on a specific case intrusion in a pipe water system. The combination of two factors is required to generate this kind of intrusion in a water supply system: on one hand the existence of at least a leak in the system; on the other hand, a pressure variation could occur during the operation of the system due to consumption variation, pump start-up or shutdown. The potential of intrusion during a dynamic or transient event is here analyzed. To obtain this objective an experimental case study of pressure transient scenario is analyzed with a small leak located nearby the transient source.

  3. A subtractive approach to interior intrusion detection system design

    International Nuclear Information System (INIS)

    Sons, R.J.; Graham, R.H. Jr.

    1986-01-01

    This paper discusses the subtractive approach to interior intrusion detection system design which assumes that all sensors are viable candidates until they are subjected to the constraints imposed by a particular facility. The constraints are determined by a sequence of questions concerning parameters such as threat definition, facility description and operation, environment, assets to be protected, security system capabilities, and cost. As a result of the questioning, some sensors will be eliminated from the candidate list, and the ''best'' set of sensors for the facility will remain. This form of questioning could be incorporated into an expert system aiding future intrusion detection system designs

  4. FuGeIDS: Fuzzy Genetic paradigms in Intrusion Detection Systems

    OpenAIRE

    Borgohain, Rajdeep

    2012-01-01

    With the increase in the number of security threats, Intrusion Detection Systems have evolved as a significant countermeasure against these threats. And as such, the topic of Intrusion Detection Systems has become one of the most prominent research topics in recent years. This paper gives an overview of the Intrusion Detection System and looks at two major machine learning paradigms used in Intrusion Detection System, Genetic Algorithms and Fuzzy Logic and how to apply them for intrusion dete...

  5. Revisiting Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.

    2009-01-01

    Intrusion detection systems (IDSs) are well-known and widely-deployed security tools to detect cyber-attacks and malicious activities in computer systems and networks. A signature-based IDS works similar to anti-virus software. It employs a signature database of known attacks, and a successful match

  6. Cyclone, Salinity Intrusion and Adaptation and Coping Measures in Coastal Bangladesh

    Directory of Open Access Journals (Sweden)

    Sebak Kumar Saha

    2017-06-01

    Full Text Available Although households in the coastal areas of Bangladesh undertake various adaptation and coping measures to minimise their vulnerability to cyclone hazards and salinity intrusion, these autonomous measures have received little attention in the past. However, the Government of Bangladesh has recently emphasised the importance of understanding these measures so that necessary interventions to make households more resilient to natural hazards and the adverse impacts of climate change can be introduced. This paper, based on secondary sources, explores adaptation and coping measures that households in the coastal areas of Bangladesh undertake to minimise their vulnerability to cyclone hazards and salinity intrusion. This paper shows that many of the adaptation and coping measures contribute to making households less vulnerable and more resilient to cyclone hazards and salinity intrusion, although some coping measures do the opposite as they reduce households’ adaptive capacities instead of improving them. This paper argues that the adaptation and coping measures that contribute to reducing households’ vulnerability to natural hazards need to be supported and guided by the government and NGOs to make them more effective. Additionally, measures that make households more vulnerable also need to be addressed by the government and NGOs, as most of these measures are related to and constrained by both poverty, and because the households have little or no access to economic opportunities.

  7. Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

    Science.gov (United States)

    Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

    2018-01-01

    Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

  8. SSHCure: A Flow-Based SSH Intrusion Detection System

    NARCIS (Netherlands)

    Hellemons, Laurens; Hendriks, Luuk; Hendriks, Luuk; Hofstede, R.J.; Sperotto, Anna; Sadre, R.; Pras, Aiko

    SSH attacks are a main area of concern for network managers, due to the danger associated with a successful compromise. Detecting these attacks, and possibly compromised victims, is therefore a crucial activity. Most existing network intrusion detection systems designed for this purpose rely on the

  9. Interpersonal pattern dynamics and adaptive behavior in multiagent neurobiological systems: conceptual model and data.

    Science.gov (United States)

    Passos, Pedro; Araújo, Duarte; Davids, Keith; Gouveia, Luis; Serpa, Sidónio; Milho, João; Fonseca, Sofia

    2009-10-01

    Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker-defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

  10. An adaptive structure data acquisition system using a graphical-based programming language

    Science.gov (United States)

    Baroth, Edmund C.; Clark, Douglas J.; Losey, Robert W.

    1992-01-01

    An example of the implementation of data fusion using a PC and a graphical programming language is discussed. A schematic of the data acquisition system and user interface panel for an adaptive structure test are presented. The computer programs (a series of icons 'wired' together) are also discussed. The way in which using graphical-based programming software to control a data acquisition system can simplify analysis of data, promote multidisciplinary interaction, and provide users a more visual key to understanding their data are shown.

  11. Nuclear data needs for non-intrusive inspection

    International Nuclear Information System (INIS)

    Smith, D. L.; Michlich, B. J.

    2000-01-01

    Various nuclear-based techniques are being explored for use in non-intrusive inspection. Their development is motivated by the need to prevent the proliferation of nuclear weapons, to thwart trafficking in illicit narcotics, to stop the transport of explosives by terrorist organizations, to characterize nuclear waste, and to deal with various other societal concerns. Non-intrusive methods are sought in order to optimize inspection speed, to minimize damage to packages and containers, to satisfy environmental, health and safety requirements, to adhere to legal requirements, and to avoid inconveniencing the innocent. These inspection techniques can be grouped into two major categories: active and passive. They almost always require the use of highly penetrating radiation and therefore are generally limited to neutrons and gamma rays. Although x-rays are widely employed for these purposes, their use does not constitute nuclear technology and therefore is not discussed here. This paper examines briefly the basic concepts associated with nuclear inspection and investigates the related nuclear data needs. These needs are illustrated by considering four of the methods currently being developed and tested

  12. Poseidon: a 2-tier Anomaly-based Network Intrusion Detection System

    NARCIS (Netherlands)

    Bolzoni, D.; Zambon, Emmanuele; Etalle, Sandro; Hartel, Pieter H.; Cole, Jack; Wolthusen, Stephen D.

    We present Poseidon, a new anomaly based intrusion detection system. Poseidon is payload-based, and presents a two-tier architecture: the first stage consists of a Self-Organizing Map, while the second one is a modified PAYL system. Our benchmarks on the 1999 DARPA data set show a higher detection

  13. A Partially Distributed Intrusion Detection System for Wireless Sensor Networks

    Science.gov (United States)

    Cho, Eung Jun; Hong, Choong Seon; Lee, Sungwon; Jeon, Seokhee

    2013-01-01

    The increasing use of wireless sensor networks, which normally comprise several very small sensor nodes, makes their security an increasingly important issue. They can be practically and efficiently secured using intrusion detection systems. Conventional security mechanisms are not usually applicable due to the sensor nodes having limitations of computational power, memory capacity, and battery power. Therefore, specific security systems should be designed to function under constraints of energy or memory. A partially distributed intrusion detection system with low memory and power demands is proposed here. It employs a Bloom filter, which allows reduced signature code size. Multiple Bloom filters can be combined to reduce the signature code for each Bloom filter array. The mechanism could then cope with potential denial of service attacks, unlike many previous detection systems with Bloom filters. The mechanism was evaluated and validated through analysis and simulation.

  14. A Partially Distributed Intrusion Detection System for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Eung Jun Cho

    2013-11-01

    Full Text Available The increasing use of wireless sensor networks, which normally comprise several very small sensor nodes, makes their security an increasingly important issue. They can be practically and efficiently secured using intrusion detection systems. Conventional security mechanisms are not usually applicable due to the sensor nodes having limitations of computational power, memory capacity, and battery power. Therefore, specific security systems should be designed to function under constraints of energy or memory. A partially distributed intrusion detection system with low memory and power demands is proposed here. It employs a Bloom filter, which allows reduced signature code size. Multiple Bloom filters can be combined to reduce the signature code for each Bloom filter array. The mechanism could then cope with potential denial of service attacks, unlike many previous detection systems with Bloom filters. The mechanism was evaluated and validated through analysis and simulation.

  15. Securing Cloud Computing from Different Attacks Using Intrusion Detection Systems

    Directory of Open Access Journals (Sweden)

    Omar Achbarou

    2017-03-01

    Full Text Available Cloud computing is a new way of integrating a set of old technologies to implement a new paradigm that creates an avenue for users to have access to shared and configurable resources through internet on-demand. This system has many common characteristics with distributed systems, hence, the cloud computing also uses the features of networking. Thus the security is the biggest issue of this system, because the services of cloud computing is based on the sharing. Thus, a cloud computing environment requires some intrusion detection systems (IDSs for protecting each machine against attacks. The aim of this work is to present a classification of attacks threatening the availability, confidentiality and integrity of cloud resources and services. Furthermore, we provide literature review of attacks related to the identified categories. Additionally, this paper also introduces related intrusion detection models to identify and prevent these types of attacks.

  16. Preventing Point-of-Sale System Intrusions

    Science.gov (United States)

    2014-06-01

    hours, some point-of-sale system vendors install a remote desktop environment (RDE) product on the business’s point-of-sale system. Many hackers...who target point-of-sale systems begin by gathering a list 8 of common network ports associated with well-known remote desktop products . For...acquiring and analyzing the Windows Registry hives from the live machine, are particularly useful for analyzing compromised Windows based point-of

  17. Intrusion Detection System for Applications using Linux Containers

    OpenAIRE

    Abed, Amr S.; Clancy, Charles; Levy, David S.

    2016-01-01

    Linux containers are gaining increasing traction in both individual and industrial use, and as these containers get integrated into mission-critical systems, real-time detection of malicious cyber attacks becomes a critical operational requirement. This paper introduces a real-time host-based intrusion detection system that can be used to passively detect malfeasance against applications within Linux containers running in a standalone or in a cloud multi-tenancy environment. The demonstrated ...

  18. System-level support for intrusion recovery

    NARCIS (Netherlands)

    Bacs, Andrei; Vermeulen, Remco; Slowinska, Asia; Bos, Herbert

    2013-01-01

    Recovering from attacks is hard and gets harder as the time between the initial infection and its detection increases. Which files did the attackers modify? Did any of user data depend on malicious inputs? Can I still trust my own documents or binaries? When malcode has been active for some time and

  19. Master data extraction and adaptation based on collected production data in manufacturing execution systems

    OpenAIRE

    Dimitrov, T.; Baumann, M.; Schenk, M.

    2010-01-01

    This paper presents an approach to extraction and correction of manufacturing master data, needed by Manufacturing Execution Systems (MES) to control and schedule the production. The implementation of the created schedule and the improvement of Key Performance Indicators depends strongly on the quality of the master data. The master data of most enterprises ages or the enterprises cannot fully provide it, because a highly manual expense for statistical analysis and administration is needed. T...

  20. Enhancing Trust Management for Wireless Intrusion Detection via Traffic Sampling in the Era of Big Data

    DEFF Research Database (Denmark)

    Meng, Weizhi; Li, Wenjuan; Su, Chunhua

    2017-01-01

    many kinds of information among sensors, whereas such network is vulnerable to a wide range of attacks, especially insider attacks, due to its natural environment and inherent unreliable transmission. To safeguard its security, intrusion detection systems (IDSs) are widely adopted in a WSN to defend...... against insider attacks through implementing proper trustbased mechanisms. However, in the era of big data, sensors may generate excessive information and data, which could degrade the effectiveness of trust computation. In this paper, we focus on this challenge and propose a way of combining Bayesian......-based trust management with traffic sampling for wireless intrusion detection under a hierarchical structure. In the evaluation, we investigate the performance of our approach in both a simulated and a real network environment. Experimental results demonstrate that packet-based trust management would become...

  1. Network Intrusion Detection through Stacking Dilated Convolutional Autoencoders

    Directory of Open Access Journals (Sweden)

    Yang Yu

    2017-01-01

    Full Text Available Network intrusion detection is one of the most important parts for cyber security to protect computer systems against malicious attacks. With the emergence of numerous sophisticated and new attacks, however, network intrusion detection techniques are facing several significant challenges. The overall objective of this study is to learn useful feature representations automatically and efficiently from large amounts of unlabeled raw network traffic data by using deep learning approaches. We propose a novel network intrusion model by stacking dilated convolutional autoencoders and evaluate our method on two new intrusion detection datasets. Several experiments were carried out to check the effectiveness of our approach. The comparative experimental results demonstrate that the proposed model can achieve considerably high performance which meets the demand of high accuracy and adaptability of network intrusion detection systems (NIDSs. It is quite potential and promising to apply our model in the large-scale and real-world network environments.

  2. Stable neural-network-based adaptive control for sampled-data nonlinear systems.

    Science.gov (United States)

    Sun, F; Sun, Z; Woo, P Y

    1998-01-01

    For a class of multiinput-multioutput (MIMO) sampled-data nonlinear systems with unknown dynamic nonlinearities, a stable neural-network (NN)-based adaptive control approach which is an integration of an NN approach and the adaptive implementation of the variable structure control with a sector, is developed. The sampled-data nonlinear system is assumed to be controllable and its state vector is available for measurement. The variable structure control with a sector serves two purposes. One is to force the system state to be within the state region in which the NN's are used when the system goes out of neural control; and the other is to provide an additional control until the system tracking error metric is controlled inside the sector within the network approximation region. The proof of a complete stability and a tracking error convergence is given and the setting of the sector and the NN parameters is discussed. It is demonstrated that the asymptotic error of the system can be made dependent only on inherent network approximation errors and the frequency range of unmodeled dynamics. Simulation studies of a two-link manipulator show the effectiveness of the proposed control approach.

  3. Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

    Science.gov (United States)

    Mitra, Sunanda; Pemmaraju, Surya

    1992-01-01

    Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

  4. Intrusion detection systems: complement to firewall security system ...

    African Journals Online (AJOL)

    The main purpose with firewall is to protect against unauthorized external attacks but it will normally leave the network unprotected from internal attacks or intrusions. Fire walls and access control have been the most important components used in order to secure network and its resources. They work to prevent attacks from ...

  5. Attack Pattern Analysis Framework for a Multiagent Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Krzysztof Juszczyszyn

    2008-08-01

    Full Text Available The paper proposes the use of attack pattern ontology and formal framework for network traffic anomalies detection within a distributed multi-agent Intrusion Detection System architecture. Our framework assumes ontology-based attack definition and distributed processing scheme with exchange of communicates between agents. The role of traffic anomalies detection was presented then it has been discussed how some specific values characterizing network communication can be used to detect network anomalies caused by security incidents (worm attack, virus spreading. Finally, it has been defined how to use the proposed techniques in distributed IDS using attack pattern ontology.

  6. Hybrid Intrusion Detection System for DDoS Attacks

    Directory of Open Access Journals (Sweden)

    Özge Cepheli

    2016-01-01

    Full Text Available Distributed denial-of-service (DDoS attacks are one of the major threats and possibly the hardest security problem for today’s Internet. In this paper we propose a hybrid detection system, referred to as hybrid intrusion detection system (H-IDS, for detection of DDoS attacks. Our proposed detection system makes use of both anomaly-based and signature-based detection methods separately but in an integrated fashion and combines the outcomes of both detectors to enhance the overall detection accuracy. We apply two distinct datasets to our proposed system in order to test the detection performance of H-IDS and conclude that the proposed hybrid system gives better results than the systems based on nonhybrid detection.

  7. Nuclear-power-plant perimeter-intrusion alarm systems

    International Nuclear Information System (INIS)

    Halsey, D.J.

    1982-04-01

    Timely intercept of an intruder requires the examination of perimeter barriers and sensors in terms of reliable detection, immediate assessment and prompt response provisions. Perimeter security equipment and operations must at the same time meet the requirements of the Code of Federal Regulations, 10 CFR 73.55 with some attention to the performance and testing figures of Nuclear Regulatory Guide 5.44, Revision 2, May 1980. A baseline system is defined which recommends a general approach to implementing perimeter security elements: barriers, lighting, intrusion detection, alarm assessment. The baseline approach emphasizes cost/effectiveness achieved by detector layering and logic processing of alarm signals to produce reliable alarms and low nuisance alarm rates. A cost benefit of layering along with video assessment is reduction in operating expense. The concept of layering is also shown to minimize testing costs where detectability performance as suggested by Regulatory Guide 5.44 is to be performed. Synthesis of the perimeter intrusion alarm system and limited testing of CCTV and Video Motion Detectors (VMD), were performed at E-Systems, Greenville Division, Greenville, Texas during 1981

  8. Nuclear-power-plant perimeter-intrusion alarm systems

    Energy Technology Data Exchange (ETDEWEB)

    Halsey, D.J.

    1982-04-01

    Timely intercept of an intruder requires the examination of perimeter barriers and sensors in terms of reliable detection, immediate assessment and prompt response provisions. Perimeter security equipment and operations must at the same time meet the requirements of the Code of Federal Regulations, 10 CFR 73.55 with some attention to the performance and testing figures of Nuclear Regulatory Guide 5.44, Revision 2, May 1980. A baseline system is defined which recommends a general approach to implementing perimeter security elements: barriers, lighting, intrusion detection, alarm assessment. The baseline approach emphasizes cost/effectiveness achieved by detector layering and logic processing of alarm signals to produce reliable alarms and low nuisance alarm rates. A cost benefit of layering along with video assessment is reduction in operating expense. The concept of layering is also shown to minimize testing costs where detectability performance as suggested by Regulatory Guide 5.44 is to be performed. Synthesis of the perimeter intrusion alarm system and limited testing of CCTV and Video Motion Detectors (VMD), were performed at E-Systems, Greenville Division, Greenville, Texas during 1981.

  9. Data mining methods application in reflexive adaptation realization in e-learning systems

    Directory of Open Access Journals (Sweden)

    A. S. Bozhday

    2017-01-01

    Full Text Available In recent years, e-learning technologies are rapidly gaining momentum in their evolution. In this regard, issues related to improving the quality of software for virtual educational systems are becoming topical: increasing the period of exploitation of programs, increasing their reliability and flexibility. The above characteristics directly depend on the ability of the software system to adapt to changes in the domain, environment and user characteristics. In some cases, this ability is reduced to the timely optimization of the program’s own interfaces and data structure. At present, several approaches to creating mechanisms for self-optimization of software systems are known, but all of them have an insufficient degree of formalization and, as a consequence, weak universality. The purpose of this work is to develop the basics of the technology of self-optimization of software systems in the structure of e-learning. The proposed technology is based on the formulated and formalized principle of reflexive adaptation of software, applicable to a wide class of software systems and based on the discovery of new knowledge in the behavioral products of the system.To solve this problem, methods of data mining were applied. Data mining allows finding regularities in the functioning of software systems, which may not be obvious at the stage of their development. Finding such regularities and their subsequent analysis will make it possible to reorganize the structure of the system in a more optimal way and without human intervention, which will prolong the life cycle of the software and reduce the costs of its maintenance. Achieving this effect is important for e-learning systems, since they are quite expensive.The main results of the work include: the proposed classification of software adaptation mechanisms, taking into account the latest trends in the IT field in general and in the field of e-learning in particular; Formulation and formalization of

  10. Hydrodynamic modeling of the intrusion phenomenon in water distribution systems; Modelacion hidrodinamica del fenomeno de intrusion en tuberia de abastecimiento

    Energy Technology Data Exchange (ETDEWEB)

    Lopez-Jimenez, Petra Amparo; Mora-Rodriguez, Jose de Jesus; Perez-Garcia, Rafael; Martinez-Solano, F. Javier [Universidad Politecnica de Valencia (Spain)

    2008-10-15

    This paper describes a strategy for the hydrodynamic modeling of the pathogen intrusion phenomenon in water distribution systems by the combination of a breakage with a depression situation. This scenario will be modeled computationally and experimentally. The phenomenon to be represented by both simulations is the same: the entrance of an external volume into the circulation of a main volume, known as a pathogen intrusion, as long as the main volume is potable water. To this end, a prototype and a computational model based on Computational Fluid Dynamics (CFD) are used, which allow visualizing the fields of speeds and pressures in a simulated form. With the comparison of the results of both models, conclusions will be drawn on the detail of the studied pathogen intrusion phenomenon. [Spanish] En el presente documento se describe una estrategia de modelacion del fenomeno hidrodinamico de la intrusion patogena en redes de distribucion de agua por combinacion de una rotura con una situacion de depresion. Este escenario sera modelado computacional y experimentalmente. El fenomeno que se desea representar con ambas simulaciones es el mismo: la entrada de un caudal externo a una conduccion para la que circula un caudal principal, denominado intrusion patogena, siempre y cuando el caudal principal sea agua potable. Para ello se dispone de un prototipo y un modelo computacional basado en la Dinamica de Fluidos Computacional (DFC de aqui en adelante), que permite visualizar los campos de velocidades y presiones de forma simulada. Con la comparacion de los resultados de ambos modelos se extraeran conclusiones sobre el detalle del fenomeno de la intrusion patogena estudiado.

  11. Semantic intrusion detection with multisensor data fusion using ...

    Indian Academy of Sciences (India)

    2016-08-26

    Aug 26, 2016 ... A multisensor-based IDS enables identification of the intrusion patterns semantically by correlating the events and context information provided by multiple sensors. ... R Bhargavi1 V Vaidehi1. Department of Information Technology, Madras Institute of Technology, Anna University, Chennai 600 044, India ...

  12. Industrial Control System Process-Oriented Intrusion Detection (iPoid) Algorithm

    Science.gov (United States)

    2016-08-01

    SUBJECT TERMS supervisory control and data acquisition ( SCADA ), Modbus, industrial control system, intrusion detection system 16. SECURITY...Dependencies 3 2.3 iPoid Rules Format 3 2.3.1 Individual Function-Rule Format 4 2.3.2 Individual Value-Rule Format 6 2.3.3 Updating Modbus Inspection Rules...enable users to dynamically update the inspection rules without restarting Bro. This avoids a risk of Bro missing packets on the wire. Fig. 2

  13. A Metrics-Based Approach to Intrusion Detection System Evaluation for Distributed Real-Time Systems

    National Research Council Canada - National Science Library

    Fink, G

    2002-01-01

    ...) computer facilities to select the best intrusion detection system for their facilities. The metrics herein are the subset of our general metric set that particularly impact real-time and distributed processing issues...

  14. Evolution of optically nondestructive and data-non-intrusive credit card verifiers

    Science.gov (United States)

    Sumriddetchkajorn, Sarun; Intaravanne, Yuttana

    2010-04-01

    Since the deployment of the credit card, the number of credit card fraud cases has grown rapidly with a huge amount of loss in millions of US dollars. Instead of asking more information from the credit card's holder or taking risk through payment approval, a nondestructive and data-non-intrusive credit card verifier is highly desirable before transaction begins. In this paper, we review optical techniques that have been proposed and invented in order to make the genuine credit card more distinguishable than the counterfeit credit card. Several optical approaches for the implementation of credit card verifiers are also included. In particular, we highlight our invention on a hyperspectral-imaging based portable credit card verifier structure that offers a very low false error rate of 0.79%. Other key features include low cost, simplicity in design and implementation, no moving part, no need of an additional decoding key, and adaptive learning.

  15. HPNAIDM: The High-Performance Network Anomaly/Intrusion Detection and Mitigation System

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Yan [Northwesten University

    2013-12-05

    Identifying traffic anomalies and attacks rapidly and accurately is critical for large network operators. With the rapid growth of network bandwidth, such as the next generation DOE UltraScience Network, and fast emergence of new attacks/virus/worms, existing network intrusion detection systems (IDS) are insufficient because they: • Are mostly host-based and not scalable to high-performance networks; • Are mostly signature-based and unable to adaptively recognize flow-level unknown attacks; • Cannot differentiate malicious events from the unintentional anomalies. To address these challenges, we proposed and developed a new paradigm called high-performance network anomaly/intrustion detection and mitigation (HPNAIDM) system. The new paradigm is significantly different from existing IDSes with the following features (research thrusts). • Online traffic recording and analysis on high-speed networks; • Online adaptive flow-level anomaly/intrusion detection and mitigation; • Integrated approach for false positive reduction. Our research prototype and evaluation demonstrate that the HPNAIDM system is highly effective and economically feasible. Beyond satisfying the pre-set goals, we even exceed that significantly (see more details in the next section). Overall, our project harvested 23 publications (2 book chapters, 6 journal papers and 15 peer-reviewed conference/workshop papers). Besides, we built a website for technique dissemination, which hosts two system prototype release to the research community. We also filed a patent application and developed strong international and domestic collaborations which span both academia and industry.

  16. Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection

    Directory of Open Access Journals (Sweden)

    Jayakumar Kaliappan

    2015-01-01

    Full Text Available An intrusion detection system (IDS helps to identify different types of attacks in general, and the detection rate will be higher for some specific category of attacks. This paper is designed on the idea that each IDS is efficient in detecting a specific type of attack. In proposed Multiple IDS Unit (MIU, there are five IDS units, and each IDS follows a unique algorithm to detect attacks. The feature selection is done with the help of genetic algorithm. The selected features of the input traffic are passed on to the MIU for processing. The decision from each IDS is termed as local decision. The fusion unit inside the MIU processes all the local decisions with the help of majority voting rule and makes the final decision. The proposed system shows a very good improvement in detection rate and reduces the false alarm rate.

  17. Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection.

    Science.gov (United States)

    Kaliappan, Jayakumar; Thiagarajan, Revathi; Sundararajan, Karpagam

    2015-01-01

    An intrusion detection system (IDS) helps to identify different types of attacks in general, and the detection rate will be higher for some specific category of attacks. This paper is designed on the idea that each IDS is efficient in detecting a specific type of attack. In proposed Multiple IDS Unit (MIU), there are five IDS units, and each IDS follows a unique algorithm to detect attacks. The feature selection is done with the help of genetic algorithm. The selected features of the input traffic are passed on to the MIU for processing. The decision from each IDS is termed as local decision. The fusion unit inside the MIU processes all the local decisions with the help of majority voting rule and makes the final decision. The proposed system shows a very good improvement in detection rate and reduces the false alarm rate.

  18. A Survey of Artificial Immune System Based Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Hua Yang

    2014-01-01

    Full Text Available In the area of computer security, Intrusion Detection (ID is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS. The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs. This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted.

  19. A survey of artificial immune system based intrusion detection.

    Science.gov (United States)

    Yang, Hua; Li, Tao; Hu, Xinlei; Wang, Feng; Zou, Yang

    2014-01-01

    In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted.

  20. Automatic Extraction and Coordination of Audit Data and Features for Intrusion and Damage Assessment

    National Research Council Canada - National Science Library

    Ye, Nong

    2006-01-01

    .... We create a new attack-norm separation approach to developing detection models for building cyber sensors monitoring and identifying intrusion data characteristics at various points along the path...

  1. Attacks and intrusion detection in wireless sensor networks of industrial SCADA systems

    Science.gov (United States)

    Kamaev, V. A.; Finogeev, A. G.; Finogeev, A. A.; Parygin, D. S.

    2017-01-01

    The effectiveness of automated process control systems (APCS) and supervisory control and data acquisition systems (SCADA) information security depends on the applied protection technologies of transport environment data transmission components. This article investigates the problems of detecting attacks in wireless sensor networks (WSN) of SCADA systems. As a result of analytical studies, the authors developed the detailed classification of external attacks and intrusion detection in sensor networks and brought a detailed description of attacking impacts on components of SCADA systems in accordance with the selected directions of attacks.

  2. The Use of Adaptive Traffic Signal Systems Based on Floating Car Data

    Directory of Open Access Journals (Sweden)

    Vittorio Astarita

    2017-01-01

    Full Text Available This paper presents a simple concept which has not been, up to now, thoroughly explored in scientific research: the use of information coming from the network of Internet connected mobile devices (on vehicles to regulate traffic light systems. Three large-scale changes are going to shape the future of transportation and could lead to the regulation of traffic signal system based on floating car data (FCD: (i the implementation of Internet connected cars with global navigation satellite (GNSS system receivers and the autonomous car revolution; (ii the spreading of mobile cooperative Web 2.0 and the extension to connected vehicles; (iii an increasing need for sustainability of transportation in terms of energy efficiency, traffic safety, and environmental issues. Up to now, the concept of floating car data (FCD has only been extensively used to obtain traffic information and estimate traffic parameters. Traffic lights regulation based on FCD technology has not been fully researched since the implementation requires new ideas and algorithms. This paper intends to provide a seminal insight into the important issue of adaptive traffic light based on FCD by presenting ideas that can be useful to researchers and engineers in the long-term task of developing new algorithms and systems that may revolutionize the way traffic lights are regulated.

  3. Thermal Error Modelling of the Spindle Using Data Transformation and Adaptive Neurofuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Yanlei Li

    2015-01-01

    Full Text Available This paper proposes a new method for predicting spindle deformation based on temperature data. The method introduces the adaptive neurofuzzy inference system (ANFIS, which is a neurofuzzy modeling approach that integrates the kernel and geometrical transformations. By utilizing data transformation, the number of ANFIS rules can be effectively reduced and the predictive model structure can be simplified. To build the predictive model, we first map the original temperature data to a feature space with Gaussian kernels. We then process the mapped data with the geometrical transformation and make the data gather in the square region. Finally, the transformed data are used as input to train the ANFIS. A verification experiment is conducted to evaluate the performance of the proposed method. Six Pt100 thermal resistances are used to monitor the spindle temperature, and a laser displacement sensor is used to detect the spindle deformation. Experimental results show that the proposed method can precisely predict the spindle deformation and greatly improve the thermal performance of the spindle. Compared with back propagation (BP networks, the proposed method is more suitable for complex working conditions in practical applications.

  4. INTRUSION DETECTION PREVENTION SYSTEM (IDPS PADA LOCAL AREA NETWORK (LAN

    Directory of Open Access Journals (Sweden)

    Didit Suhartono

    2015-02-01

    Full Text Available Penelitian ini berjudul “Intrusion Detection Prevention System Local Area Network (LAN” yang bertujuan untuk memproteksi jaringan dari usaha- usaha penyusupan yang dilakukan oleh seorang intruder. Metode yang digunakan pada penelitian ini adalah menggunakan metode kerangka pikir sebagai acuan dari tahap- tahap penelitian yang penulis lakukan. IDS difungsikan sebagai pendeteksi adanya serangan sesuai rule yang ada kemudian pesan peringatan disimpan dalam database dan dikirim via sms kepada seorang network administrator, sedangkan Firewall digunakan sebagai packet filtering dengan cara menentukan security policy yang dinilai penting. Hasilnya adalah ketika IDS memberikanpesan peringatan ketika ada serangan, seorang network administrator dapat memblok adanya serangan tersebut dengan cara manual dengan firewall, ataupun firewall akan memblok sendiri serangan tersebut sesuai dengan security policy yang diterapkan oleh network adminisrator sebelumnya

  5. A model for anomaly classification in intrusion detection systems

    Science.gov (United States)

    Ferreira, V. O.; Galhardi, V. V.; Gonçalves, L. B. L.; Silva, R. C.; Cansian, A. M.

    2015-09-01

    Intrusion Detection Systems (IDS) are traditionally divided into two types according to the detection methods they employ, namely (i) misuse detection and (ii) anomaly detection. Anomaly detection has been widely used and its main advantage is the ability to detect new attacks. However, the analysis of anomalies generated can become expensive, since they often have no clear information about the malicious events they represent. In this context, this paper presents a model for automated classification of alerts generated by an anomaly based IDS. The main goal is either the classification of the detected anomalies in well-defined taxonomies of attacks or to identify whether it is a false positive misclassified by the IDS. Some common attacks to computer networks were considered and we achieved important results that can equip security analysts with best resources for their analyses.

  6. Strategies to analyse data obtained from liquid intrusion experiments of loose porous materials.

    Science.gov (United States)

    Tan, Geoffrey; Mortona, David A V; Larson, Ian

    2017-10-25

    Liquid intrusion remains one of the most common methods to measure the contact angle of liquids to powders. However, as there are two unknown variables in the Washburn equation: the material constant (that is, the pore structure of the powder bed) and the contact angle of the liquid to the powder, this method requires the use of two liquids-a liquid of interest (the probe liquid) and a reference liquid. The reference liquid should, ideally, make a contact angle of 0° to the sample. However, in practice a low surface tension liquid is normally selected. This paper proposes a more standardised approach for the selection of the reference liquid based on experimental data. Additionally, a major assumption of the liquid intrusion method is that the pore structure, as measured by the material constant, C, is identical for all powder beds (provided that the same packing procedure is used for the same samples). In real systems, however, this is an approximation, and not likely to hold strictly true. Therefore, difficulties may arise with data analysis as there is a potential uncertainty in the most appropriate order to divide the gradient of the probe liquid by the gradient of the reference liquid. This paper proposes three specific methods of analysing such data, each with their own advantages and limitations. Hence, the selection of which method should be used is criteria-based, assessed on the basis of the obtained data. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  7. Clustering of noisy image data using an adaptive neuro-fuzzy system

    Science.gov (United States)

    Pemmaraju, Surya; Mitra, Sunanda

    1992-01-01

    Identification of outliers or noise in a real data set is often quite difficult. A recently developed adaptive fuzzy leader clustering (AFLC) algorithm has been modified to separate the outliers from real data sets while finding the clusters within the data sets. The capability of this modified AFLC algorithm to identify the outliers in a number of real data sets indicates the potential strength of this algorithm in correct classification of noisy real data.

  8. Pemanfaatan IPTables Sebagai Intrusion Detection System (IDS dan Intrusion Prevention System (IPS Pada Linux Server

    Directory of Open Access Journals (Sweden)

    Ery Setiyawan Jullev Atmadji

    2018-01-01

    Full Text Available Keamanan jaringan menjadi hal yang penting untuk semua industri dan perusahaan untuk melindungi data dan informasi penting yang berada didalamnnya. Perlindungan keamanan dalam suatu jaringan umumnya berbasis pada keamanan transmisi data yang dibuat dan diaplikasikan untuk membantu mengamankan suatu jaringan tertentu. Untuk lebih mengoptimalkan pengambilan keputusan maka diperlukan sebuah mesin yang mampu berkolaborasi dengan database IDS maupun IPS, sehingga tipikal serangan yang sangat beragam dapat dipetakan dengan lebih optimal. Salah satu database yang mempunyai rule yang sudah ada adalah IPTABLES, hal ini dikarenakan pada IPTABLES terdapat fungsi firewall yang mampu menangani jenis serangan yang berlipat serta masif. Server yang akan digunakan adalah server dengan sistem operasi Linux. Sedangkan database serangan IDS yang digunakan adalah database KDD 99 yang sudah diakui sebagai salah satu database serangan yang sangat kompleks. Dengan pemanfaatan IPTABLES ini maka diharapkan keamanan server akan bisa dimonitor dengan lebih optimal. IPTABLES biasanya digunakan sebagai salah satu firewall yang digunakan pada server.

  9. A Frequency-Based Approach to Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Mian Zhou

    2004-06-01

    Full Text Available Research on network security and intrusion detection strategies presents many challenging issues to both theoreticians and practitioners. Hackers apply an array of intrusion and exploit techniques to cause disruption of normal system operations, but on the defense, firewalls and intrusion detection systems (IDS are typically only effective in defending known intrusion types using their signatures, and are far less than mature when faced with novel attacks. In this paper, we adapt the frequency analysis techniques such as the Discrete Fourier Transform (DFT used in signal processing to the design of intrusion detection algorithms. We demonstrate the effectiveness of the frequency-based detection strategy by running synthetic network intrusion data in simulated networks using the OPNET software. The simulation results indicate that the proposed intrusion detection strategy is effective in detecting anomalous traffic data that exhibit patterns over time, which include several types of DOS and probe attacks. The significance of this new strategy is that it does not depend on the prior knowledge of attack signatures, thus it has the potential to be a useful supplement to existing signature-based IDS and firewalls.

  10. Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

    Directory of Open Access Journals (Sweden)

    S. Ganapathy

    2012-01-01

    Full Text Available Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.

  11. Intelligent agent-based intrusion detection system using enhanced multiclass SVM.

    Science.gov (United States)

    Ganapathy, S; Yogesh, P; Kannan, A

    2012-01-01

    Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set.

  12. Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

    Science.gov (United States)

    Ganapathy, S.; Yogesh, P.; Kannan, A.

    2012-01-01

    Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set. PMID:23056036

  13. Nuisance alarm suppression techniques for fibre-optic intrusion detection systems

    Science.gov (United States)

    Mahmoud, Seedahmed S.; Visagathilagar, Yuvaraja; Katsifolis, Jim

    2012-02-01

    The suppression of nuisance alarms without degrading sensitivity in fibre-optic intrusion detection systems is important for maintaining acceptable performance. Signal processing algorithms that maintain the POD and minimize nuisance alarms are crucial for achieving this. A level crossings algorithm is presented for suppressing torrential rain-induced nuisance alarms in a fibre-optic fence-based perimeter intrusion detection system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100 mm/hr, and intrusion events can be detected simultaneously during rain periods. The use of a level crossing based detection and novel classification algorithm is also presented demonstrating the suppression of nuisance events and discrimination of nuisance and intrusion events in a buried pipeline fibre-optic intrusion detection system. The sensor employed for both types of systems is a distributed bidirectional fibre-optic Mach Zehnder interferometer.

  14. Optic Nerve Stimulation System with Adaptive Wireless Powering and Data Telemetry

    Directory of Open Access Journals (Sweden)

    Xing Li

    2017-12-01

    Full Text Available To treat retinal degenerative diseases, a transcorneal electrical stimulation-based system is proposed, which consists of an eye implant and an external component. The eye implant is wirelessly powered and controlled by the external component to generate the required bi-polar current pattern for transcorneal stimulation with an amplitude range of 5 μA to 320 μA, a frequency range of 10 Hz to 160 Hz and a duty ratio range of 2.5% to 20%. Power delivery control includes power boosting in preparation for stimulation, and normal power regulation that adapts to both coupling and load variations. Only one pair of coils is used for both the power link and the bi-directional data link. Except for the secondary coil, the eye implant is fully integrated on chip and is fabricated using UMC (United Microelectronics Corporation, Hsinchu, Taiwan 0.13 μm complementary metal-oxide-semiconductor (CMOS process with a size of 1.5 mm × 1.5 mm. The secondary coil is fabricated on a printed circuit board (PCB with a diameter of only 4.4 mm. After coating with biocompatible silicone, the whole implant has dimensions of 6 mm in diameter with a thickness of less than 1 mm. The whole device can be put onto the sclera and beneath the eye’s conjunctiva. System functionality and electrical performance are demonstrated with measurement results.

  15. Diagnostic Indicators for Shipboard Mechanical Systems Using Non-Intrusive Load Monitoring

    National Research Council Canada - National Science Library

    McKay, Thomas D

    2006-01-01

    This thesis examines the use of Non-intrusive Load Monitoring (NILM) in auxiliary shipboard systems, such as a low pressure air system, to determine the state of equipment in larger connected systems, such as the main propulsion engines...

  16. Slick: An Intrusion Detection System for Virtualized Storage Devices

    NARCIS (Netherlands)

    Bacs, A.; Giuffrida, C.; Grill, B.; Bos, H.J.; Ossowski, Sascha

    2016-01-01

    Cloud computing is rapidly reshaping the server administration landscape. The widespread use of virtualization and the increasingly high server consolidation ratios, in particular, have introduced unprecedented security challenges for users, increasing the exposure to intrusions and opening up new

  17. The 2001 Mt. Etna eruption: new constraints on the intrusive mechanism from ground deformation data

    Science.gov (United States)

    Palano, Mimmo; González, Pablo J.

    2013-04-01

    The occurrence of seismic swarms beneath the SW flank of Mt. Etna, often observed just a few months before an eruption, has been considered as the fragile response to a magma intrusion (Bonanno et al., 2011 and reference therein). These intrusions and/or pressurization of deep magmatic bodies, have been able to significantly affect the seismic pattern within the volcano edifice, leading to a changes in the local stress field. For example, during the months preceding the 1991-1993 Mt. Etna eruption, shallow intense seismic swarms (4-6 km deep) occurring in the SW flank (e.g. Cocina et al., 1998), related to the magma intrusion before the eruption onset, were observed contemporaneously with a rotation of stress field of about 90°. A similar scenario was observed during January 1998, when a magma recharging phases induced a local rotation of stress tensor, forcing a buried fault zone located beneath the SW flank of Mt. Etna to slip as a right-lateral strike-slip fault (Bonanno et al., 2011). This fault system was forced to slip again, during late April 2001 (more than 200 events in less than 5 days; maximum Magnitude = 3.6) by the pressurization of the magmatic bodies feeding the July-August 2001 Mt. Etna eruption. Here we analyzed in detail the July-August 2001 Mt. Etna eruption as well as the dynamics preceding this event, by using a large dataset of geodetic data (GPS and synthetic aperture radar interferometry) collected between July 2000 and August 2001. References Cocina, O., Neri, G., Privitera, E. and Spampinato S., 1998. Seismogenic stress field beneath Mt. Etna South Italy and possible relationships with volcano-tectonic features. J. Volcanol. Geotherm. Res., 83, 335-348. Bonanno A., Palano M., Privitera E., Gresta S., Puglisi G., 2011. Magma intrusion mechanisms and redistribution of seismogenic stress at Mt. Etna volcano (1997-1998). Terra Nova, 23, 339-348, doi: 10.1111/j.1365-3121.2011.01019.x, 2011.

  18. A New Intrusion Detection System Based on KNN Classification Algorithm in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Wenchao Li

    2014-01-01

    abnormal nodes from normal nodes by observing their abnormal behaviors, and we analyse parameter selection and error rate of the intrusion detection system. The paper elaborates on the design and implementation of the detection system. This system has achieved efficient, rapid intrusion detection by improving the wireless ad hoc on-demand distance vector routing protocol (Ad hoc On-Demand Distance the Vector Routing, AODV. Finally, the test results show that: the system has high detection accuracy and speed, in accordance with the requirement of wireless sensor network intrusion detection.

  19. Optimizing the data acquisition rate for a remotely controllable structural monitoring system with parallel operation and self-adaptive sampling

    International Nuclear Information System (INIS)

    Sheng, Wenjuan; Guo, Aihuang; Liu, Yang; Azmi, Asrul Izam; Peng, Gang-Ding

    2011-01-01

    We present a novel technique that optimizes the real-time remote monitoring and control of dispersed civil infrastructures. The monitoring system is based on fiber Bragg gating (FBG) sensors, and transfers data via Ethernet. This technique combines parallel operation and self-adaptive sampling to increase the data acquisition rate in remote controllable structural monitoring systems. The compact parallel operation mode is highly efficient at achieving the highest possible data acquisition rate for the FBG sensor based local data acquisition system. Self-adaptive sampling is introduced to continuously coordinate local acquisition and remote control for data acquisition rate optimization. Key issues which impact the operation of the whole system, such as the real-time data acquisition rate, data processing capability, and buffer usage, are investigated. The results show that, by introducing parallel operation and self-adaptive sampling, the data acquisition rate can be increased by several times without affecting the system operating performance on both local data acquisition and remote process control

  20. System using data compression and hashing adapted for use for multimedia encryption

    Science.gov (United States)

    Coffland, Douglas R [Livermore, CA

    2011-07-12

    A system and method is disclosed for multimedia encryption. Within the system of the present invention, a data compression module receives and compresses a media signal into a compressed data stream. A data acquisition module receives and selects a set of data from the compressed data stream. And, a hashing module receives and hashes the set of data into a keyword. The method of the present invention includes the steps of compressing a media signal into a compressed data stream; selecting a set of data from the compressed data stream; and hashing the set of data into a keyword.

  1. A buried intrusion monitoring system based on high sensitivity optical fiber geophone

    Science.gov (United States)

    Li, Shujuan; Zhang, Faxiang; Zhang, Xiaolei; Sun, Zhihui; Min, Li; Wang, Chang

    2017-10-01

    A new intrusion monitoring system is designed, based on a high sensitivity fiber grating geophone and PGC interferometric demodulation. A kind of high sensitive fiber Bragg grating geophone is designed. The sensitivity of the geophone is analyzed by finite element software. The PGC interferometric demodulation algorithm is used to detect the wavelength of the geophone, to reduce the noise of the system and improve the signal-to-noise ratio. Invasive monitoring test was carried out, the personnel and vehicles invading signal were collected and analyzed. Test results show that the intrusion monitoring system based on fiber geophone can effectively identify remote intrusion, and has low false alarm rate.

  2. Network intrusion detection by the coevolutionary immune algorithm of artificial immune systems with clonal selection

    Science.gov (United States)

    Salamatova, T.; Zhukov, V.

    2017-02-01

    The paper presents the application of the artificial immune systems apparatus as a heuristic method of network intrusion detection for algorithmic provision of intrusion detection systems. The coevolutionary immune algorithm of artificial immune systems with clonal selection was elaborated. In testing different datasets the empirical results of evaluation of the algorithm effectiveness were achieved. To identify the degree of efficiency the algorithm was compared with analogs. The fundamental rules based of solutions generated by this algorithm are described in the article.

  3. Boosting Web Intrusion Detection Systems by Inferring Positive Signatures

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro

    2008-01-01

    We present a new approach to anomaly-based network intrusion detection for web applications. This approach is based on dividing the input parameters of the monitored web application in two groups: the "regular" and the "irregular" ones, and applying a new method for anomaly detection on the

  4. Tracking salinity intrusions in a coastal forested freshwater wetland system

    Science.gov (United States)

    Anand D. Jayakaran; Thomas M. Williams; William H. Conner

    2016-01-01

    Coastal forested freshwater wetlands are sentinel sites for salinity intrusions associated with large, tidally influenced, storm-driven or drought-induced incursions of estuarine waters into freshwater ecosystems. These incursions may also be exacerbated by rising sea levels associated with climate change.

  5. Novel Non-Intrusive Vibration Monitoring System for Turbopumps, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — AI Signal Research, Inc. proposes to develop a Non-Intrusive Vibration Measurement System (NI-VMS) for turbopumps which will provide effective on-board/off-board...

  6. Multi-Use Non-Intrusive Flow Characterization System (FCS), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The innovation is a Multi-Use Non-Intrusive Flow Characterization System (FCS) for densified, normal boiling point, and two-phase cryogenic flows, capable of...

  7. Computational neural network regression model for Host based Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Sunil Kumar Gautam

    2016-09-01

    Full Text Available The current scenario of information gathering and storing in secure system is a challenging task due to increasing cyber-attacks. There exists computational neural network techniques designed for intrusion detection system, which provide security to single machine and entire network's machine. In this paper, we have used two types of computational neural network models, namely, Generalized Regression Neural Network (GRNN model and Multilayer Perceptron Neural Network (MPNN model for Host based Intrusion Detection System using log files that are generated by a single personal computer. The simulation results show correctly classified percentage of normal and abnormal (intrusion class using confusion matrix. On the basis of results and discussion, we found that the Host based Intrusion Systems Model (HISM significantly improved the detection accuracy while retaining minimum false alarm rate.

  8. Multi-Use Non-Intrusive Flow Characterization System (FCS) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The product of the Phase II effort will be a Multi-Use Non-Intrusive Flow Characterization System (FCS) for densified, normal boiling point, and two-phase cryogenic...

  9. Novel Non-Intrusive Vibration Monitoring System for Turbopumps, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — ASRI proposes to develop an advanced and commercially viable Non-Intrusive Vibration Monitoring System (NI-VMS) which can provide effective on-line/off-line engine...

  10. Scalable High-Performance Parallel Design for Network Intrusion Detection Systems on Many-Core Processors

    OpenAIRE

    Jiang, Hayang; Xie, Gaogang; Salamatian, Kavé; Mathy, Laurent

    2013-01-01

    Network Intrusion Detection Systems (NIDSes) face significant challenges coming from the relentless network link speed growth and increasing complexity of threats. Both hardware accelerated and parallel software-based NIDS solutions, based on commodity multi-core and GPU processors, have been proposed to overcome these challenges. Network Intrusion Detection Systems (NIDSes) face significant challenges coming from the relentless network link speed growth and increasing complexity of threats. ...

  11. An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks.

    Science.gov (United States)

    Butun, Ismail; Ra, In-Ho; Sankar, Ravi

    2015-11-17

    In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) "downward-IDS (D-IDS)" to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) "upward-IDS (U-IDS)" to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented.

  12. An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ismail Butun

    2015-11-01

    Full Text Available In this work, an intrusion detection system (IDS framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1 “downward-IDS (D-IDS” to detect the abnormal behavior (intrusion of the subordinate (member nodes; and (2 “upward-IDS (U-IDS” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops and U-IDS (monitoring group size of the framework are evaluated and presented.

  13. When Intrusion Detection Meets Blockchain Technology: A Review

    DEFF Research Database (Denmark)

    Meng, Weizhi; Tischhauser, Elmar Wolfgang; Wang, Qingju

    2018-01-01

    With the purpose of identifying cyber threats and possible incidents, intrusion detection systems (IDSs) are widely deployed in various computer networks. In order to enhance the detection capability of a single IDS, collaborative intrusion detection networks (or collaborative IDSs) have been...... developed, which allow IDS nodes to exchange data with each other. However, data and trust management still remain two challenges for current detection architectures, which may degrade the effectiveness of such detection systems. In recent years, blockchain technology has shown its adaptability in many...... fields such as supply chain management, international payment, interbanking and so on. As blockchain can protect the integrity of data storage and ensure process transparency, it has a potential to be applied to intrusion detection domain. Motivated by this, this work provides a review regarding...

  14. Turbine system and adapter

    Energy Technology Data Exchange (ETDEWEB)

    Hogberg, Nicholas Alvin; Garcia-Crespo, Andres Jose

    2017-05-30

    A turbine system and adapter are disclosed. The adapter includes a turbine attachment portion having a first geometry arranged to receive a corresponding geometry of a wheelpost of a turbine rotor, and a bucket attachment portion having a second geometry arranged to receive a corresponding geometry of a root portion of a non-metallic turbine bucket. Another adapter includes a turbine attachment portion arranged to receive a plurality of wheelposts of a turbine rotor, and a bucket attachment portion arranged to receive a plurality of non-metallic turbine buckets having single dovetail configuration root portions. The turbine system includes a turbine rotor wheel configured to receive metal buckets, at least one adapter secured to at least one wheelpost on the turbine rotor wheel, and at least one non-metallic bucket secured to the at least one adapter.

  15. Semantic intrusion detection with multisensor data fusion using ...

    Indian Academy of Sciences (India)

    (DBMS) do not target the efficient processing of streams of events in real time. CEP which is a ... and process events in real- time so that downstream applications are driven by true, real-time intelligence (Luckham 2010). .... tiple points where the people might exist, the system uses pressure sensors. Load on each tile is.

  16. An artificial immune system for securing mobile ad hoc networks against intrusion attacks

    Science.gov (United States)

    Hortos, William S.

    2003-08-01

    operation of the route discovery and selection process in the presence of intrusive or malicious nodes. Furthermore, this pattern detection approach is suitable for the difficult problem of passive or hidden security threats. Based on the SRP features of the state vector, an artificial immune system (AIS) is constructed as a hierarchy of rules to detect different types of intrusive activity within the MANET. The pattern detection rules in the complement (nonself) space are generated in an evolutionary manner using a genetic search algorithm. The effect of the genetic search is to discern the varying levels of abnormal behavior in the MANET protocol transactions. The efficacy of the AIS technique is compared to the positive characterization method based on nearest-neighbor classification. Initial evaluations of the detection scheme are performed to validate the AIS-based method using training and test data sets, generated from intrusion scenarios simulated from various threat models and security-aware modifications to reactive MANET routing protocols. These results are reported along with a performance analysis comparing the AIS approach with competing techniques. Conclusions about the AIS application to MANETs using the SRP are discussed.

  17. Alerts Analysis and Visualization in Network-based Intrusion Detection Systems

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Dr. Li [University of Tennessee

    2010-08-01

    The alerts produced by network-based intrusion detection systems, e.g. Snort, can be difficult for network administrators to efficiently review and respond to due to the enormous number of alerts generated in a short time frame. This work describes how the visualization of raw IDS alert data assists network administrators in understanding the current state of a network and quickens the process of reviewing and responding to intrusion attempts. The project presented in this work consists of three primary components. The first component provides a visual mapping of the network topology that allows the end-user to easily browse clustered alerts. The second component is based on the flocking behavior of birds such that birds tend to follow other birds with similar behaviors. This component allows the end-user to see the clustering process and provides an efficient means for reviewing alert data. The third component discovers and visualizes patterns of multistage attacks by profiling the attacker s behaviors.

  18. Smart container UWB sensor system for situational awareness of intrusion alarms

    Science.gov (United States)

    Romero, Carlos E.; Haugen, Peter C.; Zumstein, James M.; Leach, Jr., Richard R.; Vigars, Mark L.

    2013-06-11

    An in-container monitoring sensor system is based on an UWB radar intrusion detector positioned in a container and having a range gate set to the farthest wall of the container from the detector. Multipath reflections within the container make every point on or in the container appear to be at the range gate, allowing intrusion detection anywhere in the container. The system also includes other sensors to provide false alarm discrimination, and may include other sensors to monitor other parameters, e.g. radiation. The sensor system also includes a control subsystem for controlling system operation. Communications and information extraction capability may also be included. A method of detecting intrusion into a container uses UWB radar, and may also include false alarm discrimination. A secure container has an UWB based monitoring system

  19. Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure.

    Science.gov (United States)

    Luo, Biao; Liu, Derong; Wu, Huai-Ning

    2017-10-03

    Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition Q(0)(x,a)≽ 0. To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.

  20. Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models

    DEFF Research Database (Denmark)

    Justesen, Kristian Kjær; Andreasen, Søren Juhl; Shaker, Hamid Reza

    2013-01-01

    an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model which is adapted to fit the measured performance of the H3-350 module. All the individual parts of the model are verified...... hydrogen, which is difficult and energy consuming to store and transport. The models include thermal equilibrium models of the individual components of the system. Models of the heating and cooling of the gas flows between components are also modeled and Adaptive Neuro-Fuzzy Inference System models...... of the reforming process are implemented. Models of the cooling flow of the blowers for the fuel cell and the burner which supplies process heat for the reformer are made. The two blowers have a common exhaust, which means that the two blowers influence each other’s output. The models take this into account using...

  1. A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments.

    Science.gov (United States)

    Sivasamy, Aneetha Avalappampatty; Sundan, Bose

    2015-01-01

    The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T(2) method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T(2) statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.

  2. TAD2: the first truly non-intrusive lie detection system deployed in real crime cases

    Science.gov (United States)

    Sumriddetchkajorn, Sarun; Somboonkaew, Armote

    2010-11-01

    Interrogation is an important step for seeking truth from the suspect. With the limit of the intrusive nature of the current polygraph, we show here a highly-sought-after non-intrusive lie detection system with a user-friendly interface called TAD2. The key idea behind our TAD2 is based on the analysis of far-infrared data obtained remotely from the periorbital and nostril areas of the suspect during the interrogation. In this way, measured change in skin temperature around two periorbital areas is converted to a relative blood flow velocity while a respiration pattern is simultaneously determined from the measured change in temperature around the nostril region. In addition, TAD2 is embedded with our automatic baseline assignment that is used for distinguishing the subject's response into normal or abnormal stage. In our TAD2, the officer can choose to perform one of the three standard lie detection tests, namely, a modified zone comparison test, a modified general question test, and an irrelevant & relevant test. Field test results from suspects in real crime cases are discussed.

  3. The adaptive approach for storage assignment by mining data of warehouse management system for distribution centres

    Science.gov (United States)

    Ming-Huang Chiang, David; Lin, Chia-Ping; Chen, Mu-Chen

    2011-05-01

    Among distribution centre operations, order picking has been reported to be the most labour-intensive activity. Sophisticated storage assignment policies adopted to reduce the travel distance of order picking have been explored in the literature. Unfortunately, previous research has been devoted to locating entire products from scratch. Instead, this study intends to propose an adaptive approach, a Data Mining-based Storage Assignment approach (DMSA), to find the optimal storage assignment for newly delivered products that need to be put away when there is vacant shelf space in a distribution centre. In the DMSA, a new association index (AIX) is developed to evaluate the fitness between the put away products and the unassigned storage locations by applying association rule mining. With AIX, the storage location assignment problem (SLAP) can be formulated and solved as a binary integer programming. To evaluate the performance of DMSA, a real-world order database of a distribution centre is obtained and used to compare the results from DMSA with a random assignment approach. It turns out that DMSA outperforms random assignment as the number of put away products and the proportion of put away products with high turnover rates increase.

  4. A Universal High-Performance Correlation Analysis Detection Model and Algorithm for Network Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Hongliang Zhu

    2017-01-01

    Full Text Available In big data era, the single detection techniques have already not met the demand of complex network attacks and advanced persistent threats, but there is no uniform standard to make different correlation analysis detection be performed efficiently and accurately. In this paper, we put forward a universal correlation analysis detection model and algorithm by introducing state transition diagram. Based on analyzing and comparing the current correlation detection modes, we formalize the correlation patterns and propose a framework according to data packet timing and behavior qualities and then design a new universal algorithm to implement the method. Finally, experiment, which sets up a lightweight intrusion detection system using KDD1999 dataset, shows that the correlation detection model and algorithm can improve the performance and guarantee high detection rates.

  5. Adaptive security systems -- Combining expert systems with adaptive technologies

    Energy Technology Data Exchange (ETDEWEB)

    Argo, P.; Loveland, R.; Anderson, K. [and others

    1997-09-01

    The Adaptive Multisensor Integrated Security System (AMISS) uses a variety of computational intelligence techniques to reason from raw sensor data through an array of processing layers to arrive at an assessment for alarm/alert conditions based on human behavior within a secure facility. In this paper, the authors give an overview of the system and briefly describe some of the major components of the system. This system is currently under development and testing in a realistic facility setting.

  6. Adaptive security systems -- Combining expert systems with adaptive technologies

    International Nuclear Information System (INIS)

    Argo, P.; Loveland, R.; Anderson, K.

    1997-01-01

    The Adaptive Multisensor Integrated Security System (AMISS) uses a variety of computational intelligence techniques to reason from raw sensor data through an array of processing layers to arrive at an assessment for alarm/alert conditions based on human behavior within a secure facility. In this paper, the authors give an overview of the system and briefly describe some of the major components of the system. This system is currently under development and testing in a realistic facility setting

  7. Combining Host-based and network-based intrusion detection system

    African Journals Online (AJOL)

    These attacks were simulated using hping. The proposed system is implemented in Java. The results show that the proposed system is able to detect attacks both from within (host-based) and outside sources (network-based). Key Words: Intrusion Detection System (IDS), Host-based, Network-based, Signature, Security log.

  8. RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sungwon Lee

    2009-05-01

    Full Text Available TheIP-based Ubiquitous Sensor Network (IP-USN is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System called RIDES (Robust Intrusion DEtection System for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

  9. RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

    Science.gov (United States)

    Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

    2009-01-01

    The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

  10. Harmful intrusion detection algorithm of optical fiber pre-warning system based on correlation of orthogonal polarization signals

    Science.gov (United States)

    Bi, Fukun; Feng, Chong; Qu, Hongquan; Zheng, Tong; Wang, Chonglei

    2017-09-01

    At present, advanced researches of optical fiber intrusion measurement are based on the constant false alarm rate (CFAR) algorithm. Although these conventional methods overcome the interference of non-stationary random signals, there are still a large number of false alarms in practical applications. This is because there is no specific study on orthogonal polarization signals of false alarm and intrusion. In order to further reduce false alarms, we analyze the correlation of optical fiber signals using birefringence of single-mode fiber. This paper proposes the harmful intrusion detection algorithm based on the correlation of two orthogonal polarization signals. The proposed method uses correlation coefficient to distinguish false alarms and intrusions, which can decrease false alarms. Experiments on real data, which are collected from the practical environment, demonstrate that the difference in correlation is a robust feature. Furthermore, the results show that the proposed algorithm can reduce the false alarms and ensure the detection performance when it is used in optical fiber pre-warning system (OFPS).

  11. PERFORMANCE COMPARISON FOR INTRUSION DETECTION SYSTEM USING NEURAL NETWORK WITH KDD DATASET

    Directory of Open Access Journals (Sweden)

    S. Devaraju

    2014-04-01

    Full Text Available Intrusion Detection Systems are challenging task for finding the user as normal user or attack user in any organizational information systems or IT Industry. The Intrusion Detection System is an effective method to deal with the kinds of problem in networks. Different classifiers are used to detect the different kinds of attacks in networks. In this paper, the performance of intrusion detection is compared with various neural network classifiers. In the proposed research the four types of classifiers used are Feed Forward Neural Network (FFNN, Generalized Regression Neural Network (GRNN, Probabilistic Neural Network (PNN and Radial Basis Neural Network (RBNN. The performance of the full featured KDD Cup 1999 dataset is compared with that of the reduced featured KDD Cup 1999 dataset. The MATLAB software is used to train and test the dataset and the efficiency and False Alarm Rate is measured. It is proved that the reduced dataset is performing better than the full featured dataset.

  12. Data Mining and Neural Networks Based Self-Adaptive Protection Strategies for Distribution Systems with DGs and FCLs

    Directory of Open Access Journals (Sweden)

    Wen-Jun Tang

    2018-02-01

    Full Text Available In light of the development of renewable energy and concerns over environmental protection, distributed generations (DGs have become a trend in distribution systems. In addition, fault current limiters (FCLs may be installed in such systems to prevent the short-circuit current from exceeding the capacity of the power apparatus. However, DGs and FCLs can lead to problems, the most critical of which is miscoordination in protection system. This paper proposes overcurrent protection strategies for distribution systems with DGs and FCLs. Through the proposed approach, relays with communication ability can determine their own operating states with the help of an operation setting decision tree and topology-adaptive neural network model based on data processed through continuous wavelet transform. The performance and effectiveness of the proposed protection strategies are verified by the simulation results obtained from various system topologies with or without DGs, FCLs, and load variations.

  13. An Embedded, Eight Channel, Noise Canceling, Wireless, Wearable sEMG Data Acquisition System With Adaptive Muscle Contraction Detection.

    Science.gov (United States)

    Ergeneci, Mert; Gokcesu, Kaan; Ertan, Erhan; Kosmas, Panagiotis

    2018-02-01

    Wearable technology has gained increasing popularity in the applications of healthcare, sports science, and biomedical engineering in recent years. Because of its convenient nature, the wearable technology is particularly useful in the acquisition of the physiological signals. Specifically, the (surface electromyography) sEMG systems, which measure the muscle activation potentials, greatly benefit from this technology in both clinical and industrial applications. However, the current wearable sEMG systems have several drawbacks including inefficient noise cancellation, insufficient measurement quality, and difficult integration to customized applications. Additionally, none of these sEMG data acquisition systems can detect sEMG signals (i.e., contractions), which provides a valuable environment for further studies such as human machine interaction, gesture recognition, and fatigue tracking. To this end, we introduce an embedded, eight channel, noise canceling, wireless, wearable sEMG data acquisition system with adaptive muscle contraction detection. Our design consists of two stages, which are the sEMG sensors and the multichannel data acquisition unit. For the first stage, we propose a low cost, dry, and active sEMG sensor that captures the muscle activation potentials, a data acquisition unit that evaluates these captured multichannel sEMG signals and transmits them to a user interface. In the data acquisition unit, the sEMG signals are processed through embedded, adaptive methods in order to reject the power line noise and detect the muscle contractions. Through extensive experiments, we demonstrate that our sEMG sensor outperforms a widely used commercially available product and our data acquisition system achieves 4.583 dB SNR gain with accuracy in the detection of the contractions.

  14. Identifying seawater intrusion in coastal areas by means of 1D and quasi-2D joint inversion of TDEM and VES data

    Science.gov (United States)

    Martínez-Moreno, F. J.; Monteiro-Santos, F. A.; Bernardo, I.; Farzamian, M.; Nascimento, C.; Fernandes, J.; Casal, B.; Ribeiro, J. A.

    2017-09-01

    Seawater intrusion is an increasingly widespread problem in coastal aquifers caused by climate changes -sea-level rise, extreme phenomena like flooding and droughts- and groundwater depletion near to the coastline. To evaluate and mitigate the environmental risks of this phenomenon it is necessary to characterize the coastal aquifer and the salt intrusion. Geophysical methods are the most appropriate tool to address these researches. Among all geophysical techniques, electrical methods are able to detect seawater intrusions due to the high resistivity contrast between saltwater, freshwater and geological layers. The combination of two or more geophysical methods is recommended and they are more efficient when both data are inverted jointly because the final model encompasses the physical properties measured for each methods. In this investigation, joint inversion of vertical electric and time domain soundings has been performed to examine seawater intrusion in an area within the Ferragudo-Albufeira aquifer system (Algarve, South of Portugal). For this purpose two profiles combining electrical resistivity tomography (ERT) and time domain electromagnetic (TDEM) methods were measured and the results were compared with the information obtained from exploration drilling. Three different inversions have been carried out: single inversion of the ERT and TDEM data, 1D joint inversion and quasi-2D joint inversion. Single inversion results identify seawater intrusion, although the sedimentary layers detected in exploration drilling were not well differentiated. The models obtained with 1D joint inversion improve the previous inversion due to better detection of sedimentary layer and the seawater intrusion appear to be better defined. Finally, the quasi-2D joint inversion reveals a more realistic shape of the seawater intrusion and it is able to distinguish more sedimentary layers recognised in the exploration drilling. This study demonstrates that the quasi-2D joint

  15. Technologies, Methodologies and Challenges in Network Intrusion Detection and Prevention Systems

    Directory of Open Access Journals (Sweden)

    Nicoleta STANCIU

    2013-01-01

    Full Text Available This paper presents an overview of the technologies and the methodologies used in Network Intrusion Detection and Prevention Systems (NIDPS. Intrusion Detection and Prevention System (IDPS technologies are differentiated by types of events that IDPSs can recognize, by types of devices that IDPSs monitor and by activity. NIDPSs monitor and analyze the streams of network packets in order to detect security incidents. The main methodology used by NIDPSs is protocol analysis. Protocol analysis requires good knowledge of the theory of the main protocols, their definition, how each protocol works.

  16. Complex adaptive systems ecology

    DEFF Research Database (Denmark)

    Sommerlund, Julie

    2003-01-01

    In the following, I will analyze two articles called Complex Adaptive Systems EcologyI & II (Molin & Molin, 1997 & 2000). The CASE-articles are some of the more quirkyarticles that have come out of the Molecular Microbial Ecology Group - a groupwhere I am currently making observational studies...

  17. Adapting the SpaceCube v2.0 Data Processing System for Mission-Unique Application Requirements

    Science.gov (United States)

    Petrick, David; Gill, Nat; Hasouneh, Munther; Stone, Robert; Winternitz, Luke; Thomas, Luke; Davis, Milton; Sparacino, Pietro; Flatley, Thomas

    2015-01-01

    The SpaceCube (sup TM) v2.0 system is a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. This paper provides an overview of the design architecture, flexibility, and the advantages of the modular SpaceCube v2.0 high performance data processing system for space applications. The current state of the proven SpaceCube technology is based on nine years of engineering and operations. Five systems have been successfully operated in space starting in 2008 with four more to be delivered for launch vehicle integration in 2015. The SpaceCube v2.0 system is also baselined as the avionics solution for five additional flight projects and is always a top consideration as the core avionics for new instruments or spacecraft control. This paper will highlight how this multipurpose system is currently being used to solve design challenges of three independent applications. The SpaceCube hardware adapts to new system requirements by allowing for application-unique interface cards that are utilized by reconfiguring the underlying programmable elements on the core processor card. We will show how this system is being used to improve on a heritage NASA GPS technology, enable a cutting-edge LiDAR instrument, and serve as a typical command and data handling (C&DH) computer for a space robotics technology demonstration.

  18. Adapting the SpaceCube v2.0 Data Processing System for Mission-Unique Application Requirements

    Science.gov (United States)

    Petrick, David

    2015-01-01

    The SpaceCubeTM v2.0 system is a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. This paper provides an overview of the design architecture, flexibility, and the advantages of the modular SpaceCube v2.0 high performance data processing system for space applications. The current state of the proven SpaceCube technology is based on nine years of engineering and operations. Five systems have been successfully operated in space starting in 2008 with four more to be delivered for launch vehicle integration in 2015. The SpaceCube v2.0 system is also baselined as the avionics solution for five additional flight projects and is always a top consideration as the core avionics for new instruments or spacecraft control. This paper will highlight how this multipurpose system is currently being used to solve design challenges of three independent applications. The SpaceCube hardware adapts to new system requirements by allowing for application-unique interface cards that are utilized by reconfiguring the underlying programmable elements on the core processor card. We will show how this system is being used to improve on a heritage NASA GPS technology, enable a cutting-edge LiDAR instrument, and serve as a typical command and data handling (CDH) computer for a space robotics technology demonstration.

  19. Functional requirements with survey results for integrated intrusion detection and access control annunciator systems

    Energy Technology Data Exchange (ETDEWEB)

    Arakaki, L.H.; Monaco, F.M.

    1995-09-01

    This report contains the guidance Functional Requirements for an Integrated Intrusion Detection and Access Control Annunciator System, and survey results of selected commercial systems. The survey questions were based upon the functional requirements; therefore, the results reflect which and sometimes how the guidance recommendations were met.

  20. ATLANTIDES: An Architecture for Alert Verification in Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Crispo, Bruno; Etalle, Sandro

    2007-01-01

    We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network

  1. A gray-box DPDA-based intrusion detection technique using system-call monitoring

    NARCIS (Netherlands)

    Jafarian, Jafar Haadi; Abbasi, Ali; Safaei Sheikhabadi, Siavash

    2011-01-01

    In this paper, we present a novel technique for automatic and efficient intrusion detection based on learning program behaviors. Program behavior is captured in terms of issued system calls augmented with point-of-system-call information, and is modeled according to an efficient deterministic

  2. ATLANTIDES: Automatic Configuration for Alert Verification in Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Crispo, B.; Etalle, Sandro

    2008-01-01

    We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network

  3. ATLANTIDES: An Architecture for Alert Verification in Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Crispo, Bruno; Etalle, Sandro

    We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network

  4. A fuzzy logic based network intrusion detection system for predicting the TCP SYN flooding attack

    CSIR Research Space (South Africa)

    Mkuzangwe, Nenekazi NP

    2017-04-01

    Full Text Available presents a fuzzy logic based network intrusion detection system to predict neptune which is a type of a Transmission Control Protocol Synchronized (TCP SYN) flooding attack. The performance of the proposed fuzzy logic based system is compared to that of a...

  5. Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

    International Nuclear Information System (INIS)

    Gonzalez, J.; Ruiz, M.; Barrera, E.; Lopez, J.M.; Arcas, G. de; Vega, J.

    2010-01-01

    The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications.

  6. Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems.

    Science.gov (United States)

    Laftah Al-Yaseen, Wathiq; Ali Othman, Zulaiha; Ahmad Nazri, Mohd Zakree

    2015-01-01

    Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy.

  7. Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems

    Directory of Open Access Journals (Sweden)

    Wathiq Laftah Al-Yaseen

    2015-01-01

    Full Text Available Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS. The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy.

  8. Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data

    Directory of Open Access Journals (Sweden)

    Epstein Richard H

    2011-01-01

    Full Text Available Abstract Background No systematic process has previously been described for a needs assessment that identifies the operating room (OR management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. Methods A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1. Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS data for most scenarios (43 of 45. Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Results Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of

  9. Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data.

    Science.gov (United States)

    Dexter, Franklin; Wachtel, Ruth E; Epstein, Richard H

    2011-01-07

    No systematic process has previously been described for a needs assessment that identifies the operating room (OR) management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1). Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS) data for most scenarios (43 of 45). Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of individualized assessments. Our technical advance is the

  10. Calibrating a Salt Water Intrusion Model with Time-Domain Electromagnetic Data

    DEFF Research Database (Denmark)

    Herckenrath, Daan; Odlum, Nick; Nenna, Vanessa

    2013-01-01

    are transformed to an electrical resistivity model, after which a geophysical forward response is calculated and compared with the measured geophysical data. This approach was applied for a field site in Santa Cruz County, California, where a time-domain electromagnetic (TDEM) dataset was collected......Salt water intrusion models are commonly used to support groundwater resource management in coastal aquifers. Concentration data used for model calibration are often sparse and limited in spatial extent. With airborne and ground-based electromagnetic surveys, electrical resistivity models can...

  11. Panacea: Automating Attack Classification for Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro; Hartel, Pieter H.; Kirda, E.; Jha, S.; Balzarotti, D.

    Anomaly-based intrusion detection systems are usually criticized because they lack a classication of attack, thus security teams have to manually inspect any raised alert to classify it. We present a new approach, Panacea, to automatically and systematically classify attacks detected by an

  12. Panacea: Automating Attack Classification for Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro; Hartel, Pieter H.

    2009-01-01

    Anomaly-based intrusion detection systems are usually criticized because they lack a classication of attack, thus security teams have to manually inspect any raised alert to classify it. We present a new approach, Panacea, to automatically and systematically classify attacks detected by an

  13. AN ENERGY EFFICIENT, MINIMALLY INTRUSIVE MULTI-SENSOR INTELLIGENT SYSTEM FOR HEALTH MONITORING OF ELDERLY PEOPLE

    OpenAIRE

    Samanta, N.; Chanda, A.K.; RoyChaudhuri, C.

    2017-01-01

    Most of the existing systems for elderly health monitoring deploy a large number of cognitive sensors including wearable sensors for physiological parameter measurement. Increasing number of sensors not only make the system power consuming and expensive but also intrusive in nature. However, there exists very limited research on power saving algorithms in such systems incorporating customer friendly features. In this paper, we report a modified health monitoring system which addresses both th...

  14. On Cyber Attacks and Signature Based Intrusion Detection for MODBUS Based Industrial Control Systems

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2014-03-01

    Full Text Available Industrial control system communication networks are vulnerable to reconnaissance, response injection, command injection, and denial of service attacks.  Such attacks can lead to an inability to monitor and control industrial control systems and can ultimately lead to system failure. This can result in financial loss for control system operators and economic and safety issues for the citizens who use these services.  This paper describes a set of 28 cyber attacks against industrial control systems which use the MODBUS application layer network protocol. The paper also describes a set of standalone and state based intrusion detection system rules which can be used to detect cyber attacks and to store evidence of attacks for post incident analysis. All attacks described in this paper were validated in a laboratory environment. The detection rate of the intrusion detection system rules presented by attack class is also presented.

  15. A modeling study of saltwater intrusion in the Andarax delta area using multiple data sources

    DEFF Research Database (Denmark)

    Antonsson, Arni Valur; Engesgaard, Peter Knudegaard; Jorreto, Sara

    In groundwater model development, construction of the conceptual model is one of the (initial and) critical aspects that determines the model reliability and applicability in terms of e.g. system (hydrogeological) understanding, groundwater quality predictions, and general use in water resources...... reaching saltwater intrusion in the area. Furthermore, the geological information obtained from these boreholes laid a foundation for a new hydrogeological conceptual model of the area, which we aim to assess in this simulation study.Appraisal of the conceptual model of the Andarax delta area is conducted...

  16. A Self-Adaptive Wireless Sensor Network Coverage Method for Intrusion Tolerance Based on Trust Value

    Directory of Open Access Journals (Sweden)

    Zuo Chen

    2015-01-01

    Full Text Available The sensor is quite easily attacked or invaded during the process of the node coverage optimization. It is a great challenge to make sure that the wireless sensor network could still carry out a secure communication and reliable coverage under the condition of being attacked. Therefore, this paper proposes a network coverage method for intrusion tolerance based on trust value of nodes by combining the trust value model with the reliable coverage optimization. It first estimates trust value of nodes through which to regulate the perception radius and decision-making radius. Furthermore, this algorithm also combines the classical methods of wireless network coverage, such as GSO and PSO, to realize the networks coverage of invasive tolerant sensor. After comparing with the conventional single cover mechanism, it can improve the security and coverage rate of network under the condition of invasion. The simulation results verify the effectiveness of the algorithm.

  17. Design and Implementation of a Smart LED Lighting System Using a Self Adaptive Weighted Data Fusion Algorithm

    Directory of Open Access Journals (Sweden)

    Wen-Tsai Sung

    2013-12-01

    Full Text Available This work aims to develop a smart LED lighting system, which is remotely controlled by Android apps via handheld devices, e.g., smartphones, tablets, and so forth. The status of energy use is reflected by readings displayed on a handheld device, and it is treated as a criterion in the lighting mode design of a system. A multimeter, a wireless light dimmer, an IR learning remote module, etc. are connected to a server by means of RS 232/485 and a human computer interface on a touch screen. The wireless data communication is designed to operate in compliance with the ZigBee standard, and signal processing on sensed data is made through a self adaptive weighted data fusion algorithm. A low variation in data fusion together with a high stability is experimentally demonstrated in this work. The wireless light dimmer as well as the IR learning remote module can be instructed directly by command given on the human computer interface, and the reading on a multimeter can be displayed thereon via the server. This proposed smart LED lighting system can be remotely controlled and self learning mode can be enabled by a single handheld device via WiFi transmission. Hence, this proposal is validated as an approach to power monitoring for home appliances, and is demonstrated as a digital home network in consideration of energy efficiency.

  18. Ku-Band Data-Communication Adapter

    Science.gov (United States)

    Schadelbauer, Steve

    1995-01-01

    Data-communication adapter circuit on single printed-circuit board serves as general-purpose interface between personal computer and satellite communication system. Designed as direct interface with Ku-band data-communication system for payloads on space shuttle, also used with any radio-frequency transmission systems. Readily installed in almost any personal computer via widely used Industry Standard Architecture (ISA) bus.

  19. Comparison of empirical models with intensively observed data for prediction of salt intrusion in the Sumjin River estuary, Korea

    Directory of Open Access Journals (Sweden)

    D. C. Shaha

    2009-06-01

    Full Text Available Performance of empirical models has been compared with extensively observed data to determine the most suitable model for prediction of salt intrusion in the Sumjin River estuary, Korea. Intensive measurements of salt intrusion were taken at high and low waters during both spring and neap tide in each season from August 2004 to April 2007. The stratification parameter varied with the distance along the estuary, tidal period and freshwater discharge, indicating that the Sumjin River estuary experiences a transition from partially- or well-mixed during spring tide to stratified during neap tide. The salt intrusion length at high water varied from 13.4 km in summer 2005 to 25.6 km in autumn 2006. The salt intrusion mostly depends on the freshwater discharge rather than spring-neap tidal oscillation. Analysis of three years observed salinity data indicates that the scale of the salt intrusion length in the Sumjin River estuary is proportional to the river discharge to the −1/5 power. Four empirical models have been applied to the Sumjin River estuary to explore the most suitable model for prediction of the salt intrusion length. Comparative results show that the Nguyen and Savenije (2006 model, developed under both partially- and well-mixed estuaries, performs best of all models studied (relative error of 4.6%. The model was also applied under stratified neap tide conditions, with a relative error of 5.2%, implying applicability of this model under stratified conditions as well.

  20. Model-Data Fusion and Adaptive Sensing for Large Scale Systems: Applications to Atmospheric Release Incidents

    Science.gov (United States)

    Madankan, Reza

    All across the world, toxic material clouds are emitted from sources, such as industrial plants, vehicular traffic, and volcanic eruptions can contain chemical, biological or radiological material. With the growing fear of natural, accidental or deliberate release of toxic agents, there is tremendous interest in precise source characterization and generating accurate hazard maps of toxic material dispersion for appropriate disaster management. In this dissertation, an end-to-end framework has been developed for probabilistic source characterization and forecasting of atmospheric release incidents. The proposed methodology consists of three major components which are combined together to perform the task of source characterization and forecasting. These components include Uncertainty Quantification, Optimal Information Collection, and Data Assimilation. Precise approximation of prior statistics is crucial to ensure performance of the source characterization process. In this work, an efficient quadrature based method has been utilized for quantification of uncertainty in plume dispersion models that are subject to uncertain source parameters. In addition, a fast and accurate approach is utilized for the approximation of probabilistic hazard maps, based on combination of polynomial chaos theory and the method of quadrature points. Besides precise quantification of uncertainty, having useful measurement data is also highly important to warranty accurate source parameter estimation. The performance of source characterization is highly affected by applied sensor orientation for data observation. Hence, a general framework has been developed for the optimal allocation of data observation sensors, to improve performance of the source characterization process. The key goal of this framework is to optimally locate a set of mobile sensors such that measurement of textit{better} data is guaranteed. This is achieved by maximizing the mutual information between model predictions

  1. Complex adaptive systems ecology

    DEFF Research Database (Denmark)

    Sommerlund, Julie

    2003-01-01

    In the following, I will analyze two articles called Complex Adaptive Systems EcologyI & II (Molin & Molin, 1997 & 2000). The CASE-articles are some of the more quirkyarticles that have come out of the Molecular Microbial Ecology Group - a groupwhere I am currently making observational studies....... They are the result of acooperation between Søren Molin, professor in the group, and his brother, JanMolin, professor at Department of Organization and Industrial Sociology atCopenhagen Business School. The cooperation arises from the recognition that bothmicrobial ecology and sociology/organization theory works...

  2. Sequence-aware intrusion detection in industrial control systems

    NARCIS (Netherlands)

    Caselli, M.; Zambon, Emmanuele; Kargl, Frank; Zhou, Jianying; Jones, D.

    Nowadays, several threats endanger cyber-physical systems. Among these systems, industrial control systems (ICS) operating on critical infrastructures have been proven to be an attractive target for attackers. The case of Stuxnet has not only showed that ICSs are vulnerable to cyber-attacks, but

  3. Adaptive Data Processing Technique for Lidar-Assisted Control to Bridge the Gap between Lidar Systems and Wind Turbines: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Schlipf, David; Raach, Steffen; Haizmann, Florian; Cheng, Po Wen; Fleming, Paul; Scholbrock, Andrew, Krishnamurthy, Raghu; Boquet, Mathieu

    2015-12-14

    This paper presents first steps toward an adaptive lidar data processing technique crucial for lidar-assisted control in wind turbines. The prediction time and the quality of the wind preview from lidar measurements depend on several factors and are not constant. If the data processing is not continually adjusted, the benefit of lidar-assisted control cannot be fully exploited, or can even result in harmful control action. An online analysis of the lidar and turbine data are necessary to continually reassess the prediction time and lidar data quality. In this work, a structured process to develop an analysis tool for the prediction time and a new hardware setup for lidar-assisted control are presented. The tool consists of an online estimation of the rotor effective wind speed from lidar and turbine data and the implementation of an online cross correlation to determine the time shift between both signals. Further, initial results from an ongoing campaign in which this system was employed for providing lidar preview for feed-forward pitch control are presented.

  4. An adaptive map-matching algorithm based on hierarchical fuzzy system from vehicular GPS data.

    Directory of Open Access Journals (Sweden)

    Jinjun Tang

    Full Text Available An improved hierarchical fuzzy inference method based on C-measure map-matching algorithm is proposed in this paper, in which the C-measure represents the certainty or probability of the vehicle traveling on the actual road. A strategy is firstly introduced to use historical positioning information to employ curve-curve matching between vehicle trajectories and shapes of candidate roads. It improves matching performance by overcoming the disadvantage of traditional map-matching algorithm only considering current information. An average historical distance is used to measure similarity between vehicle trajectories and road shape. The input of system includes three variables: distance between position point and candidate roads, angle between driving heading and road direction, and average distance. As the number of fuzzy rules will increase exponentially when adding average distance as a variable, a hierarchical fuzzy inference system is then applied to reduce fuzzy rules and improve the calculation efficiency. Additionally, a learning process is updated to support the algorithm. Finally, a case study contains four different routes in Beijing city is used to validate the effectiveness and superiority of the proposed method.

  5. An Intelligent Tutor for Intrusion Detection on Computer Systems.

    Science.gov (United States)

    Rowe, Neil C.; Schiavo, Sandra

    1998-01-01

    Describes an intelligent tutor incorporating a program using artificial-intelligence planning methods to generate realistic audit files reporting actions of simulated users and intruders of a UNIX system, and a program simulating the system afterwards that asks students to inspect the audit and fix problems. Experiments show that students using…

  6. A Distributed Signature Detection Method for Detecting Intrusions in Sensor Systems

    Directory of Open Access Journals (Sweden)

    Won Woo Ro

    2013-03-01

    Full Text Available Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on theWu–Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors.

  7. A distributed signature detection method for detecting intrusions in sensor systems.

    Science.gov (United States)

    Kim, Ilkyu; Oh, Doohwan; Yoon, Myung Kuk; Yi, Kyueun; Ro, Won Woo

    2013-03-25

    Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on the Wu-Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors.

  8. Rb-Sr ages and palaeomagnetic data for some Angolan alkaline intrusives

    International Nuclear Information System (INIS)

    Allsopp, H.L.; Hargraves, R.B.

    1985-01-01

    New Rb-Sr age measurements are reported for a number of intrusives from Angola. Data for the Njoio and Tchivira nepheline syenite bodies yield mineral isochrons indicating ages of 104,3+-0,8 Ma and 130,8+-1,4 Ma respectively. Palaeomagnetic studies on the same occurrences gave marginal and scattered results respectively. Micas from the Camafuca crater-facies kimberlite yielded and apparent age of 1 822+-151 Ma, a result that is far in excess of the Tertiary (or younger) age inferred for this pipe. Similarly conflicting data were obtained for the Nova Lisboa kimberlite. It is likely that older crustal micas incorporated in the kimberlite breccias are responsible for the anomalous ages reported on the kimberlites. Satisfactory palaeomagnetic data are reported for the Zenza and Bailundu occurrences, not dated by the Rb-Sr method. A convenient K-Ar age of 80+-0,8 Ma was obtainable for Zenza

  9. An intrusion prevention system as a proactive security mechanism in network infrastructure

    Directory of Open Access Journals (Sweden)

    Dulanović Nenad

    2008-01-01

    Full Text Available A properly configured firewall is a good starting point in securing a computer network. However, complex network environments that involve higher number of participants and endpoints require better security infrastructure. Intrusion Detection Systems (IDS, proposed as a solution to perimeter defense, have many open problems and it is clear that better solutions must be found. Due to many unsolved problems associated with IDS, Intrusion Prevention Systems (IPS are introduced. The main idea in IPS is to be proactive. This paper gives an insight of Cobrador Bouncer IPS implementation. System architecture is given and three different Bouncer IPS deployment modes are presented. The Bouncer IPS as a proactive honeypot is also discussed.

  10. Adaptable Web Modules to Stimulate Active Learning in Engineering Hydrology using Data and Model Simulations of Three Regional Hydrologic Systems

    Science.gov (United States)

    Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.

    2013-12-01

    server-based system. Open source web technologies and community-based tools are used to facilitate wide dissemination and adaptation by diverse, independent institutions. The new hydrologic learning modules are based on recent developments in hydrologic modeling, data, and resources. The modules are embedded in three regional-scale ecosystems, Coastal Louisiana, Florida Everglades, and Utah Great Salt Lake Basin. These sites provide a wealth of hydrologic concepts and scenarios that can be used in most water resource and hydrology curricula. The study develops several learning modules based on the three hydro-systems covering subjects such as: water-budget analysis, effects of human and natural changes, climate-hydrology teleconnections, and water-resource management scenarios. The new developments include an instructional interface to give critical guidance and support to the learner and an instructor's guide containing adaptation and implementation procedures to assist instructors in adopting and integrating the material into courses and provide a consistent experience. The design of the new hydrologic education developments will be transferable to independent institutions and adaptable both instructionally and technically through a server system capable of supporting additional developments by the educational community.

  11. Rate Adaptive OFDMA Communication Systems

    International Nuclear Information System (INIS)

    Abdelhakim, M.M.M.

    2009-01-01

    Due to the varying nature of the wireless channels, adapting the transmission parameters, such as code rate, modulation order and power, in response to the channel variations provides a significant improvement in the system performance. In the OFDM systems, Per-Frame adaptation (PFA) can be employed where the transmission variables are fixed over a given frame and may change from one frame to the other. Subband (tile) loading offers more degrees of adaptation such that each group of carriers (subband) uses the same transmission parameters and different subbands may use different parameters. Changing the code rate for each tile in the same frame, results in transmitting multiple codewords (MCWs) for a single frame. In this thesis a scheme is proposed for adaptively changing the code rate of coded OFDMA systems via changing the puncturing rate within a single codeword (SCW). In the proposed structure, the data is encoded with the lowest available code rate then it is divided among the different tiles where it is punctured adaptively based on some measure of the channel quality for each tile. The proposed scheme is compared against using multiple codewords (MCWs) where the different code rates for the tiles are obtained using separate encoding processes. For bit interleaved coded modulation architecture two novel interleaving methods are proposed, namely the puncturing dependant interleaver (PDI) and interleaved puncturing (IntP), which provide larger interleaving depth. In the PDI method the coded bits with the same rate over different tiles are grouped for interleaving. In IntP structure the interleaving is performed prior to puncturing. The performance of the adaptive puncturing technique is investigated under constant bit rate constraint and variable bit rate. Two different adaptive modulation and coding (AMC) selection methods are examined for variable bit rate adaptive system. The first is a recursive scheme that operates directly on the SNR whereas the second

  12. PENERAPAN NAIVE BAYES PADA INTRUSION DETECTION SYSTEM DENGAN DISKRITISASI VARIABEL

    Directory of Open Access Journals (Sweden)

    I Nyoman Trisna Wirawan

    2015-07-01

    Pada penelitian ini akan dibahas mengenai penerapan naive bayes classifier dengan menggunakan pemilihan atribut berdasarkan pada korelasi serta preprocessing data dengan diskritisasi dengan menggunakan metode mean/standar deviasi untuk atribut kontinu dengan menggunakan 3-interval dan 5-interval. Hasil percobaan menunjukan bahwa penerapan naive bayes pada klasifikasi data yang telah melewati proses diskritisasi mampu memberikan akurasi hingga 89% dengan running time rata-rata adalah 31 detik.

  13. Implementation of Karp-Rabin string matching algorithm in reconfigurable hardware for network intrusion prevention system

    Science.gov (United States)

    Botwicz, Jakub; Buciak, Piotr; Sapiecha, Piotr

    2006-03-01

    Intrusion Prevention Systems (IPSs) have become widely recognized as a powerful tool and an important element of IT security safeguards. The essential feature of network IPSs is searching through network packets and matching multiple strings, that are fingerprints of known attacks. String matching is highly resource consuming and also the most significant bottleneck of IPSs. In this article an extension of the classical Karp-Rabin algorithm and its implementation architectures were examined. The result is a software, which generates a source code of a string matching module in hardware description language, that could be easily used to create an Intrusion Prevention System implemented in reconfigurable hardware. The prepared module matches the complete set of Snort IPS signatures achieving throughput of over 2 Gbps on an Altera Stratix I1 evaluation board. The most significant advantage of the proposed architecture is that the update of the patterns database does not require reconfiguration of the circuitry.

  14. Optimal Placement and Sizing of PV-STATCOM in Power Systems Using Empirical Data and Adaptive Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Reza Sirjani

    2018-03-01

    Full Text Available Solar energy is a source of free, clean energy which avoids the destructive effects on the environment that have long been caused by power generation. Solar energy technology rivals fossil fuels, and its development has increased recently. Photovoltaic (PV solar farms can only produce active power during the day, while at night, they are completely idle. At the same time, though, active power should be supported by reactive power. Reactive power compensation in power systems improves power quality and stability. The use during the night of a PV solar farm inverter as a static synchronous compensator (or PV-STATCOM device has recently been proposed which can improve system performance and increase the utility of a PV solar farm. In this paper, a method for optimal PV-STATCOM placement and sizing is proposed using empirical data. Considering the objectives of power loss and cost minimization as well as voltage improvement, two sub-problems of placement and sizing, respectively, are solved by a power loss index and adaptive particle swarm optimization (APSO. Test results show that APSO not only performs better in finding optimal solutions but also converges faster compared with bee colony optimization (BCO and lightening search algorithm (LSA. Installation of a PV solar farm, STATCOM, and PV-STATCOM in a system are each evaluated in terms of efficiency and cost.

  15. An Analysis of Security System for Intrusion in Smartphone Environment

    Directory of Open Access Journals (Sweden)

    Maya Louk

    2014-01-01

    Full Text Available There are many malware applications in Smartphone. Smartphone’s users may become unaware if their data has been recorded and stolen by intruders via malware. Smartphone—whether for business or personal use—may not be protected from malwares. Thus, monitoring, detecting, tracking, and notification (MDTN have become the main purpose of the writing of this paper. MDTN is meant to enable Smartphone to prevent and reduce the number of cybercrimes. The methods are shown to be effective in protecting Smartphone and isolating malware and sending warning in the form of notification to the user about the danger in progress. In particular, (a MDTN process is possible and will be enabled for Smartphone environment. (b The methods are shown to be an advanced security for private sensitive data of the Smartphone user.

  16. Strategic adaptation to new electoral systems

    OpenAIRE

    Selb, Peter

    2012-01-01

    How quickly, to what extent and under what conditions do voters and elites adapt to new electoral institutions in order to not waste their votes and effort on hopeless competitors? A latent-curve model of strategic adaptation is developed and fitted to district-level election data from Spain. The extent of strategic adaptation is generally found to vary with the strength of the electoral system. However, grave ethnic tensions are demonstrated to seriously retard adaptation even under favourab...

  17. A framework for implementing a Distributed Intrusion Detection System (DIDS) with interoperabilty and information analysis

    OpenAIRE

    Davicino, Pablo; Echaiz, Javier; Ardenghi, Jorge Raúl

    2011-01-01

    Computer Intrusion Detection Systems (IDS) are primarily designed to protect availability, condentiality and integrity of critical information infrastructures. A Distributed IDS (DIDS) consists of several IDS over a large network(s), all of which communicate with each other, with a central server or with a cluster of servers that facilitates advanced network monitoring. In a distributed environment, DIDS are implemented using cooperative intelligent sensors distributed across the network(s). ...

  18. Enhanced Intrusion Detection System for Input Validation Attacks in Web Application

    OpenAIRE

    Puspendra Kumar; R. K. Pateriya

    2013-01-01

    Internet continues to expand exponentially and access to the Internet become more prevalent in our daily life but at the same time web application are becoming most attractive targets for hacker and cyber criminals. This paper presents an enhanced intrusion detection system approach for detecting input validation attacks in the web application. The existing IDS for Input validation attacks are language dependent. The proposed IDS is language independent i.e. it works for any web application d...

  19. MFIRE-2: A Multi Agent System for Flow-Based Intrusion Detection Using Stochastic Search

    Science.gov (United States)

    2012-03-01

    users access to a server or services. The SYN flood attack is a common example of a network level denial of service attack. It is easy to launch and... TCP /IP connection establishment mechanism and floods the server’s pending connection queue. Viruses, Trojan Horses, and Worms—A virus is a program...is a complete sweep of all ports: the services can log the sender IP address and Intrusion detection systems can raise an alarm. TCP SYN scan— SYN

  20. Cybersecurity managing systems, conducting testing, and investigating intrusions

    CERN Document Server

    Mowbray, Thomas J

    2013-01-01

    A must-have, hands-on guide for working in the cybersecurity profession Cybersecurity involves preventative methods to protect information from attacks. It requires a thorough understanding of potential threats, such as viruses and other malicious code, as well as system vulnerability and security architecture. This essential book addresses cybersecurity strategies that include identity management, risk management, and incident management, and also serves as a detailed guide for anyone looking to enter the security profession. Doubling as the text for a cybersecurity course, it is also a usef

  1. Instant OSSEC host-based intrusion detection system

    CERN Document Server

    Lhotsky, Brad

    2013-01-01

    Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. A fast-paced, practical guide to OSSEC-HIDS that will help you solve host-based security problems.This book is great for anyone concerned about the security of their servers-whether you are a system administrator, programmer, or security analyst, this book will provide you with tips to better utilize OSSEC-HIDS. Whether you're new to OSSEC-HIDS or a seasoned veteran, you'll find something in this book you can apply today!This book assumes some knowledge of basic security concepts an

  2. Resilient Control and Intrusion Detection for SCADA Systems

    Science.gov (United States)

    2014-05-01

    square-error ( MMSE ) with a consistent observation vector dimension to have a lower computational load. Note the noise covariance of fused measurement...change times, or this distribution is nonstationary (i.e. it doesn’t have an invariant mean nor variance). This is particularly meaningful for our 51...j are time- invariant and are denoted by A. Then we can combine all t linear systems (7.1) into a single equation B = AX , (7.2) where B = [b1b2

  3. Design and implementation of an intrusion detection system based on IPv6 protocol

    Science.gov (United States)

    Liu, Bin; Li, Zhitang; Li, Yao; Li, Zhanchun

    2005-11-01

    Network intrusion detection systems (NIDS) are important parts of network security architecture. Although many NIDS have been proposed, there is little effort to expand the current set of NIDS to support IPv6 protocol. This paper presents the design and implementation of a Network-based Intrusion Detection System that supports both IPv6 protocol and IPv4 protocol. It characters rules based logging to perform content pattern matching and detect a variety of attacks and probes from IPv4 and IPv6.There are four primary subsystems to make it up: packet capture, packet decoder, detection engine, and logging and alerting subsystem. A new approach to packet capture that combined NAPI with MMAP is proposed in this paper. The test results show that the efficiency of packet capture can be improved significantly by this method. Several new attack tools for IPv6 have been developed for intrusion detection evaluation. Test shows that more than 20 kinds of IPv6 attacks can be detected by this system and it also has a good performance under heavy traffic load.

  4. Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models

    DEFF Research Database (Denmark)

    Justesen, Kristian Kjær; Andreasen, Søren Juhl; Shaker, Hamid Reza

    2014-01-01

    an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model which is adapted to fit the measured performance of the H3-350 module. All the individual parts of the model are verified...

  5. Adaptivity in Professional Printing Systems

    NARCIS (Netherlands)

    Verriet, J.H.; Basten, T; Hamberg, R.; Reckers, F.J.; Somers, L.

    2013-01-01

    There is a constant pressure on developers of embedded systems to simultaneously increase system functionality and to decrease development costs. Aviable way to obtain a better system performance with the same physical hardware is adaptivity: a system should be able to adapt itself to dynamically

  6. On-line detection of Escherichia coli intrusion in a pilot-scale drinking water distribution system.

    Science.gov (United States)

    Ikonen, Jenni; Pitkänen, Tarja; Kosse, Pascal; Ciszek, Robert; Kolehmainen, Mikko; Miettinen, Ilkka T

    2017-08-01

    Improvements in microbial drinking water quality monitoring are needed for the better control of drinking water distribution systems and for public health protection. Conventional water quality monitoring programmes are not always able to detect a microbial contamination of drinking water. In the drinking water production chain, in addition to the vulnerability of source waters, the distribution networks are prone to contamination. In this study, a pilot-scale drinking-water distribution network with an on-line monitoring system was utilized for detecting bacterial intrusion. During the experimental Escherichia coli intrusions, the contaminant was measured by applying a set of on-line sensors for electric conductivity (EC), pH, temperature (T), turbidity, UV-absorbance at 254 nm (UVAS SC) and with a device for particle counting. Monitored parameters were compared with the measured E. coli counts using the integral calculations of the detected peaks. EC measurement gave the strongest signal compared with the measured baseline during the E. coli intrusion. Integral calculations showed that the peaks in the EC, pH, T, turbidity and UVAS SC data were detected corresponding to the time predicted. However, the pH and temperature peaks detected were barely above the measured baseline and could easily be mixed with the background noise. The results indicate that on-line monitoring can be utilized for the rapid detection of microbial contaminants in the drinking water distribution system although the peak interpretation has to be performed carefully to avoid being mixed up with normal variations in the measurement data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. ℋ2-optimal control of an adaptive optics system. Pt.I: data-driven modeling of the wavefront disturbance

    NARCIS (Netherlands)

    Hinnen, K.J.G.; Verhaegen, M.; Doelman, N.J.

    2005-01-01

    Even though the wavefront distortion introduced by atmospheric turbulence is a dynamic process, its temporal evolution is usually neglected in the adaptive optics (AO) control design. Most AO control systems consider only the spatial correlation in a separate wavefront reconstruction step. By

  8. Intrusion Detection System Requirements. A Capabilities Description in Terms of the Network Monitoring and Assessment Module of CSAP21

    National Research Council Canada - National Science Library

    Metcalf, Therese R; LaPadula, Leonard J

    2000-01-01

    ...) module of the Computer Security Assistance Program for the Twenty-First Century (CSAP21) architecture. The advantage of this approach is that it provides a global and comprehensive context in which to describe intrusion detection system...

  9. Intrusion detection sensors

    International Nuclear Information System (INIS)

    Williams, J.D.

    1978-07-01

    Intrusion detection sensors are an integral part of most physical security systems. Under the sponsorship of the U.S. Department of Energy, Office of Safeguards and Security, Sandia Laboratories has conducted a survey of available intrusion detection sensors and has tested a number of different sensors. An overview of these sensors is provided. This overview includes (1) the operating principles of each type of sensor, (2) unique sensor characteristics, (3) desired sensor improvements which must be considered in planning an intrusion detection system, and (4) the site characteristics which affect the performance of both exterior and interior sensors. Techniques which have been developed to evaluate various intrusion detection sensors are also discussed

  10. Intrusion Learning: An Overview of an Emergent Discipline

    Directory of Open Access Journals (Sweden)

    Tony Bailetti

    2016-02-01

    Full Text Available The purpose of this article is to provide a definition of intrusion learning, identify its distinctive aspects, and provide recommendations for advancing intrusion learning as a practice domain. The authors define intrusion learning as the collection of online network algorithms that learn from and monitor streaming network data resulting in effective intrusion-detection methods for enabling the security and resiliency of enterprise systems. The network algorithms build on advances in cyber-defensive and cyber-offensive capabilities. Intrusion learning is an emerging domain that draws from machine learning, intrusion detection, and streaming network data. Intrusion learning offers to significantly enhance enterprise security and resiliency through augmented perimeter defense and may mitigate increasing threats facing enterprise perimeter protection. The article will be of interest to researchers, sponsors, and entrepreneurs interested in enhancing enterprise security and resiliency.

  11. An Adaptable Seismic Data Format

    Science.gov (United States)

    Krischer, Lion; Smith, James; Lei, Wenjie; Lefebvre, Matthieu; Ruan, Youyi; de Andrade, Elliott Sales; Podhorszki, Norbert; Bozdağ, Ebru; Tromp, Jeroen

    2016-11-01

    We present ASDF, the Adaptable Seismic Data Format, a modern and practical data format for all branches of seismology and beyond. The growing volume of freely available data coupled with ever expanding computational power opens avenues to tackle larger and more complex problems. Current bottlenecks include inefficient resource usage and insufficient data organization. Properly scaling a problem requires the resolution of both these challenges, and existing data formats are no longer up to the task. ASDF stores any number of synthetic, processed or unaltered waveforms in a single file. A key improvement compared to existing formats is the inclusion of comprehensive meta information, such as event or station information, in the same file. Additionally, it is also usable for any non-waveform data, for example, cross-correlations, adjoint sources or receiver functions. Last but not least, full provenance information can be stored alongside each item of data, thereby enhancing reproducibility and accountability. Any data set in our proposed format is self-describing and can be readily exchanged with others, facilitating collaboration. The utilization of the HDF5 container format grants efficient and parallel I/O operations, integrated compression algorithms and check sums to guard against data corruption. To not reinvent the wheel and to build upon past developments, we use existing standards like QuakeML, StationXML, W3C PROV and HDF5 wherever feasible. Usability and tool support are crucial for any new format to gain acceptance. We developed mature C/Fortran and Python based APIs coupling ASDF to the widely used SPECFEM3D_GLOBE and ObsPy toolkits.

  12. Towards Adaptive Educational Assessments: Predicting Student Performance using Temporal Stability and Data Analytics in Learning Management Systems

    Energy Technology Data Exchange (ETDEWEB)

    Thakur, Gautam [ORNL; Olama, Mohammed M [ORNL; McNair, Wade [ORNL; Sukumar, Sreenivas R [ORNL

    2014-01-01

    Data-driven assessments and adaptive feedback are becoming a cornerstone research in educational data analytics and involve developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the students and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present our efforts in using data analytics that enable educationists to design novel data-driven assessment and feedback mechanisms. In order to achieve this objective, we investigate temporal stability of students grades and perform predictive analytics on academic data collected from 2009 through 2013 in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for assessments and predicting student outcomes such as students scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total Grade Point Average(GPA) at the same term they enrolled in the course. Second, time series models in both frequency and time domains are applied to characterize the progression as well as overall projections of the grades. In particular, the model analyzed the stability as well as fluctuation of grades among students during the collegiate years (from freshman to senior) and disciplines. Third, Logistic Regression and Neural Network predictive models are used to identify students as early as possible who are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. The time series analysis indicates that assessments and continuous feedback are critical for freshman and sophomores (even with easy courses) than for seniors, and those assessments may be

  13. Systematic adaptation of data delivery

    Science.gov (United States)

    Bakken, David Edward

    2016-02-02

    This disclosure describes, in part, a system management component for use in a power grid data network to systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription and the system management component may adjust the data rates in real-time to ensure that the power grid data network does not become overloaded and/or fail. In one example, subscriptions with lower priorities may have their quality of service adjusted before subscriptions with higher priorities. In each instance, the quality of service may be maintained, even if reduced, to meet or exceed the minimum acceptable quality of service for the subscription.

  14. Farming System Evolution and Adaptive Capacity: Insights for Adaptation Support

    Directory of Open Access Journals (Sweden)

    Jami L. Dixon

    2014-02-01

    Full Text Available Studies of climate impacts on agriculture and adaptation often provide current or future assessments, ignoring the historical contexts farming systems are situated within. We investigate how historical trends have influenced farming system adaptive capacity in Uganda using data from household surveys, semi-structured interviews, focus-group discussions and observations. By comparing two farming systems, we note three major findings: (1 similar trends in farming system evolution have had differential impacts on the diversity of farming systems; (2 trends have contributed to the erosion of informal social and cultural institutions and an increasing dependence on formal institutions; and (3 trade-offs between components of adaptive capacity are made at the farm-scale, thus influencing farming system adaptive capacity. To identify the actual impacts of future climate change and variability, it is important to recognize the dynamic nature of adaptation. In practice, areas identified for further adaptation support include: shift away from one-size-fits-all approach the identification and integration of appropriate modern farming method; a greater focus on building inclusive formal and informal institutions; and a more nuanced understanding regarding the roles and decision-making processes of influential, but external, actors. More research is needed to understand farm-scale trade-offs and the resulting impacts across spatial and temporal scales.

  15. Human intrusion

    International Nuclear Information System (INIS)

    Hora, S.; Neill, R.; Williams, R.; Bauser, M.; Channell, J.

    1993-01-01

    This paper focused on the possible approaches to evaluating the impacts of human intrusion on nuclear waste disposal. Several major issues were reviewed. First, it was noted that human intrusion could be addressed either quantitatively through performance assessments or qualitatively through design requirements. Second, it was decided that it was impossible to construct a complete set of possible future human intrusion scenarios. Third, the question of when the effect of possible human intrusion should be considered, before or after site selection was reviewed. Finally, the time frame over which human intrusion should be considered was discussed

  16. Integrated Adaptive Analysis and Visualization of Satellite Network Data Project

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to develop a system that enables integrated and adaptive analysis and visualization of satellite network management data. Integrated analysis and...

  17. Adaptive control for chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Hua Changchun E-mail: cch@ysu.edu.cn; Guan Xinping

    2004-10-01

    Control problem of chaotic system is investigated via adaptive method. A fairly simple adaptive controller is constructed, which can control chaotic systems to unstable fixed points. The precise mathematical models of chaotic systems need not be known and only the fixed points and the dimensions of chaotic systems are required to be known. Simulations on controlling different chaotic systems are investigated and the results show the validity and feasibility of the proposed controller.

  18. Torque Control During Intrusion on Upper Central Incisor in Labial and Lingual bracket System - A 3D Finite Element Study.

    Science.gov (United States)

    Pol, Tejas R; Vandekar, Meghna; Patil, Anuradha; Desai, Sanjana; Shetty, Vikram; Hazarika, Saptarshi

    2018-01-01

    The aim of present study was to investigate the difference of torque control during intrusive force on upper central incisors with normal, under and high torque in lingual and labial orthodontic systems through 3D finite element analysis. Six 3D models of an upper right central incisor with different torque were designed in Solid Works 2006. Software ANSYS Version 16.0 was used to evaluate intrusive force on upper central incisor model . An intrusive force of 0.15 N was applied to the bracket slot in different torque models and the displacements along a path of nodes in the upper central incisor was assessed. On application of Intrusive force on under torqued upper central incisor in Labial system produce labial crown movement but in Lingual system caused lingual movement in the apical and incisal parts. The same intrusive force in normal-torqued central incisor led to a palatal movement in apical and labial displacement of incisal edge in Lingual system and a palatal displacement in apical area and a labial movement in the incisal edge in Labial systemin. In overtorqued upper central incisor, the labial crown displacement in Labial system is more than Lingual system. In labial and lingual system on application of the same forces in upper central incisor with different inclinations showed different responses. The magnitudes of torque Loss during intrusive loads in incisors with normal, under and over-torque were higher in Labial system than Lingual orthodontic appliances. Key words: FEM, lingual orthodontics, intrusion, torque control, labial bracket systems.

  19. A Comparative Analysis of the Snort and Suricata Intrusion-Detection Systems

    Science.gov (United States)

    2011-09-01

    Ubuntu 10.04 for the client machine, and for the web server with the PDF files we used a Dell Latitude laptop running Xubuntu. This test required an FTP ...service and a web server be installed and running on the intrusion-detection system server . We chose to install Vsftpd for our FTP client due to...From OISF, 2011c) The Suricata configuration file allows the user to configure which and how many threads, and how many CPUs will be involved in the

  20. ANOMALY NETWORK INTRUSION DETECTION SYSTEM BASED ON DISTRIBUTED TIME-DELAY NEURAL NETWORK (DTDNN

    Directory of Open Access Journals (Sweden)

    LAHEEB MOHAMMAD IBRAHIM

    2010-12-01

    Full Text Available In this research, a hierarchical off-line anomaly network intrusion detection system based on Distributed Time-Delay Artificial Neural Network is introduced. This research aims to solve a hierarchical multi class problem in which the type of attack (DoS, U2R, R2L and Probe attack detected by dynamic neural network. The results indicate that dynamic neural nets (Distributed Time-Delay Artificial Neural Network can achieve a high detection rate, where the overall accuracy classification rate average is equal to 97.24%.

  1. A Proposal of Protocol and Policy-Based Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Tatsuya Baba

    2004-06-01

    Full Text Available Currently, intrusion detection systems (IDSs are widely deployed in enterprise networks for detecting network attacks. Most existing commercial IDSs are based on misuse detection model. In misuse detection, although known attacks can be detected, unknown ones cannot be detected because attack signatures for unknown attacks cannot be generated. In this paper, we propose a method for detecting network attacks including unknown ones against servers such as web servers, mail servers, FTP servers, and DNS servers, using protocol specifications and site access policy. Furthermore, we propose a method to predict damage from detected attacks using neural networks.

  2. A harmful-intrusion detection method based on background reconstruction and two-dimensional K-S test in an optical fiber pre-warning system

    Science.gov (United States)

    Bi, Fukun; Zheng, Tong; Qu, Hongquan; Pang, Liping

    2016-06-01

    The key technology and main difficulty for optical fiber intrusion pre-warning systems (OFIPS) is the extraction of harmful-intrusion signals. After being processed by a phase-sensitive optical time-domain reflectometer (Φ-OTDR), vibration signals can be preliminarily extracted. Generally, these include noises and intrusions. Here, intrusions can be divided into harmful and harmless intrusions. With respect to the close study of signal characteristics, an effective extraction method of harmful intrusion is proposed in the paper. Firstly, in the part of the background reconstruction, all intrusion signals are first detected by a constant false alarm rate (CFAR). We then reconstruct the backgrounds by extracting two-part information of alarm points, time and amplitude. This ensures that the detection background consists of intrusion signals. Secondly, in the part of the two-dimensional Kolmogorov-Smirnov (K-S) test, in order to extract harmful ones from all extracted intrusions, we design a separation method. It is based on the signal characteristics of harmful intrusion, which are shorter time interval and higher amplitude. In the actual OFIPS, the detection method is used in some typical scenes, which includes a lot of harmless intrusions, for example construction sites and busy roads. Results show that we can effectively extract harmful intrusions.

  3. Distributed intrusion monitoring system with fiber link backup and on-line fault diagnosis functions

    Science.gov (United States)

    Xu, Jiwei; Wu, Huijuan; Xiao, Shunkun

    2014-12-01

    A novel multi-channel distributed optical fiber intrusion monitoring system with smart fiber link backup and on-line fault diagnosis functions was proposed. A 1× N optical switch was intelligently controlled by a peripheral interface controller (PIC) to expand the fiber link from one channel to several ones to lower the cost of the long or ultra-long distance intrusion monitoring system and also to strengthen the intelligent monitoring link backup function. At the same time, a sliding window auto-correlation method was presented to identify and locate the broken or fault point of the cable. The experimental results showed that the proposed multi-channel system performed well especially whenever any a broken cable was detected. It could locate the broken or fault point by itself accurately and switch to its backup sensing link immediately to ensure the security system to operate stably without a minute idling. And it was successfully applied in a field test for security monitoring of the 220-km-length national borderline in China.

  4. WSN-DS: A Dataset for Intrusion Detection Systems in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Iman Almomani

    2016-01-01

    Full Text Available Wireless Sensor Networks (WSN have become increasingly one of the hottest research areas in computer science due to their wide range of applications including critical military and civilian applications. Such applications have created various security threats, especially in unattended environments. To ensure the security and dependability of WSN services, an Intrusion Detection System (IDS should be in place. This IDS has to be compatible with the characteristics of WSNs and capable of detecting the largest possible number of security threats. In this paper a specialized dataset for WSN is developed to help better detect and classify four types of Denial of Service (DoS attacks: Blackhole, Grayhole, Flooding, and Scheduling attacks. This paper considers the use of LEACH protocol which is one of the most popular hierarchical routing protocols in WSNs. A scheme has been defined to collect data from Network Simulator 2 (NS-2 and then processed to produce 23 features. The collected dataset is called WSN-DS. Artificial Neural Network (ANN has been trained on the dataset to detect and classify different DoS attacks. The results show that WSN-DS improved the ability of IDS to achieve higher classification accuracy rate. WEKA toolbox was used with holdout and 10-Fold Cross Validation methods. The best results were achieved with 10-Fold Cross Validation with one hidden layer. The classification accuracies of attacks were 92.8%, 99.4%, 92.2%, 75.6%, and 99.8% for Blackhole, Flooding, Scheduling, and Grayhole attacks, in addition to the normal case (without attacks, respectively.

  5. Oxygen isotope mapping and evaluation of paleo-hydrothermal systems associated with synvolcanic intrusion and VMS deposits

    International Nuclear Information System (INIS)

    Taylor, B.E

    2001-01-01

    Whole-rock oxygen isotope mapping provides a useful method for the delineation and quantitative evaluation of paleo-hydrothermal systems associated with syn-volcanic intrusions and volcanic-associated massive sulfide (VMS) deposits. During the course of a four-year study of regional alteration systems associated with VMS Deposits, four syn-volcanic intrusive complexes in Canada were mapped using stable isotope techniques. The complexes included Noranda, Quebec; Clifford-Ben Nevis, Ontario; Snow Lake, Manitoba, and Sturgeon Lake, Ontario. This study was regional in extent, involving large areas and large numbers of whole-rock samples: Noranda (625 km 2 ;≥600 samples, plus others (total = 1198); Sturgeon Lake (525 km 2 ; 452 samples); Clifford-Ben Nevis (160 km 2 ; 251 samples); and Snow Lake (84 km 2 ; 575 samples). Isotopic data on whole-rock carbonates and hydrous minerals were also collected. The regional isotopic studies were carried out in concert with other studies on mineral assemblages and mineral composition, and on associated intrusive and extrusive rocks. The Clifford-Ben Nevis area was selected as a control area, in as much as it contains no known VMS deposits; all other areas are well-known, productive VMS districts. Oxygen isotope maps are, in a sense, thermal maps, illustrating the paleo-distribution of heat and fluids, and offering a potential aid to exploration. The isotopic data may be contoured to reveal zones of 18 O depletion and enrichment, relative to unaltered rocks. Zones of δ 18 O≤60% comprise rocks that have reacted with seawater at high (e.g., 300+ o C) temperatures. The volume of foot-wall rocks isotopically-depleted by water/rock interaction during the life of one or more episodes of submarine hydrothermal activity is proportional to the amount of heat available from the syn-volcanic intrusive center. These altered rocks comprise the reaction zone often inferred to have supplied metals and other constituents for the VMS deposits

  6. An Intrusion Detection System for the Protection of Railway Assets Using Fiber Bragg Grating Sensors

    Directory of Open Access Journals (Sweden)

    Angelo Catalano

    2014-09-01

    Full Text Available We demonstrate the ability of Fiber Bragg Gratings (FBGs sensors to protect large areas from unauthorized activities in railway scenarios such as stations or tunnels. We report on the technological strategy adopted to protect a specific depot, representative of a common scenario for security applications in the railway environment. One of the concerns in the protection of a railway area centers on the presence of rail-tracks, which cannot be obstructed with physical barriers. We propose an integrated optical fiber system composed of FBG strain sensors that can detect human intrusion for protection of the perimeter combined with FBG accelerometer sensors for protection of rail-track access. Several trials were carried out in indoor and outdoor environments. The results demonstrate that FBG strain sensors bonded under a ribbed rubber mat enable the detection of intruder break-in via the pressure induced on the mat, whereas the FBG accelerometers installed under the rails enable the detection of intruders walking close to the railroad tracks via the acoustic surface waves generated by footsteps. Based on a single enabling technology, this integrated system represents a valuable intrusion detection system for railway security and could be integrated with other sensing functionalities in the railway field using fiber optic technology.

  7. An intrusion detection system for the protection of railway assets using Fiber Bragg Grating sensors.

    Science.gov (United States)

    Catalano, Angelo; Bruno, Francesco Antonio; Pisco, Marco; Cutolo, Antonello; Cusano, Andrea

    2014-09-29

    We demonstrate the ability of Fiber Bragg Gratings (FBGs) sensors to protect large areas from unauthorized activities in railway scenarios such as stations or tunnels. We report on the technological strategy adopted to protect a specific depot, representative of a common scenario for security applications in the railway environment. One of the concerns in the protection of a railway area centers on the presence of rail-tracks, which cannot be obstructed with physical barriers. We propose an integrated optical fiber system composed of FBG strain sensors that can detect human intrusion for protection of the perimeter combined with FBG accelerometer sensors for protection of rail-track access. Several trials were carried out in indoor and outdoor environments. The results demonstrate that FBG strain sensors bonded under a ribbed rubber mat enable the detection of intruder break-in via the pressure induced on the mat, whereas the FBG accelerometers installed under the rails enable the detection of intruders walking close to the railroad tracks via the acoustic surface waves generated by footsteps. Based on a single enabling technology, this integrated system represents a valuable intrusion detection system for railway security and could be integrated with other sensing functionalities in the railway field using fiber optic technology.

  8. Effects of saltwater intrusion on pinewood vegetation using satellite ASTER data: the case study of Ravenna (Italy).

    Science.gov (United States)

    Barbarella, M; De Giglio, M; Greggio, N

    2015-04-01

    The San Vitale pinewood (Ravenna, Italy) is part of the remaining wooded areas within the southeastern Po Valley. Several studies demonstrated a widespread saltwater intrusion in the phreatic aquifer caused by natural and human factors in this area as the whole complex coastal system. Groundwater salinization affects soils and vegetation, which takes up water from the shallow aquifer. Changes in groundwater salinity induce variations of the leaf properties and vegetation cover, recognizable by satellite sensors as a response to different spectral bands. A procedure to identify stressed areas from satellite remote sensing data, reducing the expensive and time-consuming ground monitoring campaign, was developed. Multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, acquired between May 2005 and August 2005, were used to calculate Normalized Difference Vegetation Index (NDVI). Within the same vegetation type (thermophilic deciduous forest), the areas with the higher vegetation index were taken as reference to identify the most stressed areas using a statistical approach. To confirm the findings, a comparison was conducted using contemporary groundwater salinity data. The results were coherent in the areas with highest and lowest average NDVI values. Instead, to better understand the behavior of the intermediate areas, other parameters influencing vegetation (meteorological data, water table depth, and tree density) were added for the interpretation of the results.

  9. Non-intrusive appliance load monitoring system based on a modern kWh-meter

    Energy Technology Data Exchange (ETDEWEB)

    Pihala, H. [VTT Energy, Espoo (Finland). Energy Systems

    1998-12-01

    Non-intrusive appliance load monitoring (NIALM) is a fairly new method to estimate load profiles of individual electric appliances in a small building, like a household, by monitoring the whole load at a single point with one recording device without sub-meters. Appliances have special electrical characteristics, the positive and negative active and reactive power changes during the time they are switched on or off. These changes are called events and are detected with a monitoring device called an event recorder. Different NIALM-concepts developed in Europe and in the United States are generally discussed. The NIALM-concept developed in this study is based on a 3-phase, power quality monitoring kWh-meter and unique load identification algorithms. This modern kWh-meter with a serial data bus to a laptop personal computer is used as die event recorder. The NIALM-concept of this presentation shows for the first time how a kWh-meter can be used at the same time for billing, power quality and appliance end-use monitoring. An essential part of the developed NIALM-system prototype is the software of load identification algorithms which runs in an off-line personal computer. These algorithms are able to identify, with a certain accuracy, both two-state and multi-state appliances. This prototype requires manual-setup in which the naming of appliances is performed. The results of the prototype NIALMS were verified in a large, single family detached house and they were compared to the results of other prototypes in France and the United States, although this comparison is difficult because of different supply systems, appliance stock and number of tested sites. Different applications of NIALM are discussed. Gathering of load research data, verification of DSM-programs, home automation, failure analysis of appliances and security surveillance of buildings are interesting areas of NIALM. Both utilities and customers can benefit from these applications. It is possible to

  10. Research on regional intrusion prevention and control system based on target tracking

    Science.gov (United States)

    Liu, Yanfei; Wang, Jieling; Jiang, Ke; He, Yanhui; Wu, Zhilin

    2017-08-01

    In view of the fact that China’s border is very long and the border prevention and control measures are single, we designed a regional intrusion prevention and control system which based on target-tracking. The system consists of four parts: solar panel, radar, electro-optical equipment, unmanned aerial vehicle and intelligent tracking platform. The solar panel provides independent power for the entire system. The radar detects the target in real time and realizes the high precision positioning of suspicious targets, then through the linkage of electro-optical equipment, it can achieve full-time automatic precise tracking of targets. When the target appears within the range of detection, the drone will be launched to continue the tracking. The system is mainly to realize the full time, full coverage, whole process integration and active realtime control of the border area.

  11. A Dynamic Intrusion Detection System Based on Multivariate Hotelling’s T2 Statistics Approach for Network Environments

    Directory of Open Access Journals (Sweden)

    Aneetha Avalappampatty Sivasamy

    2015-01-01

    Full Text Available The ever expanding communication requirements in today’s world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling’s T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling’s T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup’99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.

  12. Confidentiality Protection of User Data and Adaptive Resource Allocation for Managing Multiple Workflow Performance in Service-Based Systems

    Science.gov (United States)

    An, Ho

    2012-01-01

    In this dissertation, two interrelated problems of service-based systems (SBS) are addressed: protecting users' data confidentiality from service providers, and managing performance of multiple workflows in SBS. Current SBSs pose serious limitations to protecting users' data confidentiality. Since users' sensitive data is sent in…

  13. Adaptive web data extraction policies

    Directory of Open Access Journals (Sweden)

    Provetti, Alessandro

    2008-12-01

    Full Text Available Web data extraction is concerned, among other things, with routine data accessing and downloading from continuously-updated dynamic Web pages. There is a relevant trade-off between the rate at which the external Web sites are accessed and the computational burden on the accessing client. We address the problem by proposing a predictive model, typical of the Operating Systems literature, of the rate-of-update of each Web source. The presented model has been implemented into a new version of the Dynamo project: a middleware that assists in generating informative RSS feeds out of traditional HTML Web sites. To be effective, i.e., make RSS feeds be timely and informative and to be scalable, Dynamo needs a careful tuning and customization of its polling policies, which are described in detail.

  14. Cyber-intrusion Auto-response and Policy Management System (CAPMS)

    Energy Technology Data Exchange (ETDEWEB)

    Lusk, Steve [ViaSat Inc., Boston, MA (United States); Lawrence, David [Duke Energy, Charlotte, NC (United States); Suvana, Prakash [Southern California Edison, Rosemead, CA (United States)

    2015-11-11

    The Cyber-intrusion Auto-response and Policy Management System (CAPMS) project was funded by a grant from the US Department of Energy (DOE) Cybersecurity for Energy Delivery Systems (CEDS) program with contributions from two partner electric utilities: Southern California Edison (SCE) and Duke Energy. The goal of the project was to demonstrate protecting smart grid assets from a cyber attack in a way that “does not impede critical energy delivery functions.” This report summarizes project goals and activities for the CAPMS project and explores what did and did not work as expected. It concludes with an assessment of possible benefits and value of the system for the future.

  15. A Hypergraph and Arithmetic Residue-based Probabilistic Neural Network for classification in Intrusion Detection Systems.

    Science.gov (United States)

    Raman, M R Gauthama; Somu, Nivethitha; Kirthivasan, Kannan; Sriram, V S Shankar

    2017-08-01

    Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous efforts by the researchers have resulted in the development of several learning models based on Artificial Neural Network (ANN) to improve the performance of the IDSs. However, there exists a tradeoff with respect to the stability of ANN architecture and the detection rate for less frequent attacks. This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS. The Helly property of Hypergraph was exploited for the identification of the optimal feature subset and the arithmetic residue of the optimal feature subset was used to train the PNN. The performance of HG AR-PNN was evaluated using KDD CUP 1999 intrusion dataset. Experimental results prove the dominance of HG AR-PNN classifier over the existing classifiers with respect to the stability and improved detection rate for less frequent attacks. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Monitoring and Assessment of Saltwater Intrusion using Geographic Information Systems (GIS), Remote Sensing and Geophysical measurements of Guimaras Island, Philippines

    Science.gov (United States)

    Hernandez, B. C. B.

    2015-12-01

    Degrading groundwater quality due to saltwater intrusion is one of the key challenges affecting many island aquifers. These islands hold limited capacity for groundwater storage and highly dependent on recharge due to precipitation. But its ease of use, natural storage and accessibility make it more vulnerable to exploitation and more susceptible to encroachment from its surrounding oceanic waters. Estimating the extent of saltwater intrusion and the state of groundwater resources are important in predicting and managing water supply options for the community. In Guimaras island, central Philippines, increasing settlements, agriculture and tourism are causing stresses on its groundwater resource. Indications of saltwater intrusion have already been found at various coastal areas in the island. A Geographic Information Systems (GIS)-based approach using the GALDIT index was carried out. This includes six parameters assessing the seawater intrusion vulnerability of each hydrogeologic setting: Groundwater occurrence, Aquifer hydraulic conductivity, Groundwater Level above sea, Distance to shore, Impact of existing intrusion and Thickness of Aquifer. To further determine the extent of intrusion, Landsat images of various thematic layers were stacked and processed for unsupervised classification and electrical resistivity tomography using a 28-electrode system with array lengths of 150 and 300 meters was conducted. The GIS index showed where the vulnerable areas are located, while the geophysical measurements and images revealed extent of seawater encroachment along the monitoring wells. These results are further confirmed by the measurements collected from the monitoring wells. This study presents baseline information on the state of groundwater resources and increase understanding of saltwater intrusion dynamics in island ecosystems by providing a guideline for better water resource management in the Philippines.

  17. Morphologic and hemodynamic analysis of dental pulp in dogs after molar intrusion with the skeletal anchorage system.

    Science.gov (United States)

    Konno, Yuichi; Daimaruya, Takayoshi; Iikubo, Masahiro; Kanzaki, Reiko; Takahashi, Ichiro; Sugawara, Junji; Sasano, Takashi

    2007-08-01

    We have successfully treated skeletal open bite by intruding posterior teeth with the skeletal anchorage system. Our aim in this study was to morphologically and hemodynamically evaluate the changes in pulp tissues when molars are radically intruded. The mandibular fourth premolars of 9 adult beagle dogs were divided into 3 groups: a sham operated group (n = 6, 3 dogs), 4-month intrusion group (n = 6, 3 dogs), and a further 4-month retention group (n = 6, 3 dogs). We evaluated the morphological changes of the pulp and dentin-the amount of vacuolar degeneration in the odontoblast layer, the predentin width and nervous continuity in the pulp tissue, and the pulpal blood-flow response evoked by electrical stimulation in the dental pulp. Extreme molar intrusion with the skeletal anchorage system caused slight degenerative changes in the pulp tissue, followed by recovery after the orthodontic force was released. Circulatory system and nervous functions were basically maintained during the intrusion, although a certain level of downregulation was observed. These morphologic and functional regressive changes in the pulp tissue after molar intrusion improved during the retention period. Histologic changes and changes in pulpal blood flow and function are reversible, even during radical intrusion of molars.

  18. Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model

    Science.gov (United States)

    Jin, Jing; Wang, Yuanqing; Xu, Liujing; Cao, Liqun; Han, Lei; Zhou, Biye; Li, Minggao

    2014-11-01

    A non-intrusive gesture recognition human-machine interaction system is proposed in this paper. In order to solve the hand positioning problem which is a difficulty in current algorithms, face detection is used for the pre-processing to narrow the search area and find user's hand quickly and accurately. Hidden Markov Model (HMM) is used for gesture recognition. A certain number of basic gesture units are trained as HMM models. At the same time, an improved 8-direction feature vector is proposed and used to quantify characteristics in order to improve the detection accuracy. The proposed system can be applied in interaction equipments without special training for users, such as household interactive television

  19. Web interactive non intrusive load disaggregation system for active demand in smart grids

    Directory of Open Access Journals (Sweden)

    G.M. Tina

    2014-12-01

    Full Text Available A Smart Grid combines the use of traditional technology with innovative digital solutions, making the management of the electricity grid more flexible. It allows for monitoring, analysis, control and communication within the supply chain to improve efficiency, reduce the energy consumption and cost, and maximize the transparency and reliability of the energy supply chain. The optimization of energy consumption in Smart Grids is possible by using an innovative system based on Non Intrusive Appliance Load Monitoring (NIALM algorithms, in which individual appliance power consumption information is disaggregated from single-point measurements, that provide a feedback in such a way to make energy more visible and more amenable to understanding and control. We contribute with an approach for monitoring consumption of electric power in households based on both a NILM algorithm, that uses a simple load signatures, and a web interactive systems that allows an active role played by users.

  20. Data-Reusing Adaptive Filtering Algorithms with Adaptive Error Constraint

    OpenAIRE

    Young-Seok Choi

    2016-01-01

    We present a family of data-reusing and affine projection algorithms. For identification of a noisy linear finite impulse response channel, a partial knowledge of a channel, especially noise, can be used to improve the performance of the adaptive filter. Motivated by this fact, the proposed scheme incorporates an estimate of a knowledge of noise. A constraint, called the adaptive noise constraint, estimates an unknown information of noise. By imposing this constraint on a...

  1. Fractal analysis of SEM images and mercury intrusion porosimetry data for the microstructural characterization of microcrystalline cellulose-based pellets

    International Nuclear Information System (INIS)

    Gomez-Carracedo, A.; Alvarez-Lorenzo, C.; Coca, R.; Martinez-Pacheco, R.; Concheiro, A.; Gomez-Amoza, J.L.

    2009-01-01

    The microstructure of theophylline pellets prepared from microcrystalline cellulose, carbopol and dicalcium phosphate dihydrate, according to a mixture design, was characterized using textural analysis of gray-level scanning electron microscopy (SEM) images and thermodynamic analysis of the cumulative pore volume distribution obtained by mercury intrusion porosimetry. Surface roughness evaluated in terms of gray-level non-uniformity and fractal dimension of pellet surface depended on agglomeration phenomena during extrusion/spheronization. Pores at the surface, mainly 1-15 μm in diameter, determined both the mechanism and the rate of theophylline release, and a strong negative correlation between the fractal geometry and the b parameter of the Weibull function was found for pellets containing >60% carbopol. Theophylline mean dissolution time from these pellets was about two to four times greater. Textural analysis of SEM micrographs and fractal analysis of mercury intrusion data are complementary techniques that enable complete characterization of multiparticulate drug dosage forms

  2. Application of the Concept of Intrusion Tolerant System for Evaluating Cyber Security Enhancements

    International Nuclear Information System (INIS)

    Lee, Chanyoung; Seong, Poong Hyun

    2016-01-01

    One of the major problems is that nuclear industry is in very early stage in dealing with cyber security issues. It is because that cyber security has received less attention compared to other safety problems. In addition, late adoption of digital I and C systems has resulted in lower level of cyber security advancements in nuclear industry than ones in other industries. For the cyber security of NPP I and C systems, many regulatory documents, guides and standards were already published. These documents include cyber security plans, methods for cyber security assessments and comprehensive set of security controls. However, methods which can help assess how much security is improved if a specific security control is applied are not included in these documents. Hence, NPP I and C system designers may encounter difficulties when trying to apply security controls with limited structure and cost. In order to provide useful information about cyber security issues including cyber security enhancements, this paper suggests a framework to evaluate how much cyber security is improved when a specific cyber security enhancement is applied in NPPs. In order to provide useful information about cyber security issues including cyber security enhancements, this paper suggests a framework to evaluate how much cyber security is improved when a specific cyber security enhancement is applied in NPPs. The extent of cyber security improvement caused by security enhancement was defined as reduction ratio of the failure probability to secure the system from cyber-attack as Eq.1. The concept of 'intrusion tolerant system' was applied to not only prevent cyber-attacks but also limit the extent of damage in this study. For applying the concept of intrusion tolerant system to NPP, the event tree was constructed with some assumptions. Cyber security improvement caused by cyber security enhancement can be estimated as Eq.3. By comparing current system to the enhanced system, it is

  3. Application of the Concept of Intrusion Tolerant System for Evaluating Cyber Security Enhancements

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Chanyoung; Seong, Poong Hyun [KAIST, Daejeon (Korea, Republic of)

    2016-10-15

    One of the major problems is that nuclear industry is in very early stage in dealing with cyber security issues. It is because that cyber security has received less attention compared to other safety problems. In addition, late adoption of digital I and C systems has resulted in lower level of cyber security advancements in nuclear industry than ones in other industries. For the cyber security of NPP I and C systems, many regulatory documents, guides and standards were already published. These documents include cyber security plans, methods for cyber security assessments and comprehensive set of security controls. However, methods which can help assess how much security is improved if a specific security control is applied are not included in these documents. Hence, NPP I and C system designers may encounter difficulties when trying to apply security controls with limited structure and cost. In order to provide useful information about cyber security issues including cyber security enhancements, this paper suggests a framework to evaluate how much cyber security is improved when a specific cyber security enhancement is applied in NPPs. In order to provide useful information about cyber security issues including cyber security enhancements, this paper suggests a framework to evaluate how much cyber security is improved when a specific cyber security enhancement is applied in NPPs. The extent of cyber security improvement caused by security enhancement was defined as reduction ratio of the failure probability to secure the system from cyber-attack as Eq.1. The concept of 'intrusion tolerant system' was applied to not only prevent cyber-attacks but also limit the extent of damage in this study. For applying the concept of intrusion tolerant system to NPP, the event tree was constructed with some assumptions. Cyber security improvement caused by cyber security enhancement can be estimated as Eq.3. By comparing current system to the enhanced system, it is

  4. The role of genetic structure in the adaptive divergence of populations experiencing saltwater intrusion due to relative sea-level rise.

    Science.gov (United States)

    Purcell, K M; Hitch, A; Martin, S; Klerks, P L; Leberg, P L

    2012-12-01

    Saltwater intrusion into estuaries creates stressful conditions for nektonic species. Previous studies have shown that Gambusia affinis populations with exposure to saline environments develop genetic adaptations for increased survival during salinity stress. Here, we evaluate the genetic structure of G. affinis populations, previously shown to have adaptations for increased salinity tolerance, and determine the impact of selection and gene flow on structure of these populations. We found that gene flow was higher between populations experiencing different salinity regimes within an estuary than between similar marsh types in different estuaries, suggesting the development of saline-tolerant phenotypes due to local adaptation. There was limited evidence of genetic structure along a salinity gradient, and only some of the genetic variation among sites was correlated with salinity. Our results suggest limited structure, combined with selection to saltwater intrusion, results in phenotypic divergence in spite of a lack of physical barriers to gene flow. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

  5. Diabetes Intrusiveness and Wellness among Elders: A Test of the Illness Intrusiveness Model

    Science.gov (United States)

    DeCoster, Vaughn A.; Killian, Tim; Roessler, Richard T.

    2013-01-01

    Using data collected from 147 predominately African American senior citizens in Arkansas, this research examined the Illness Intrusiveness Model (Devins, 1991; Devins & Seland, 1987; Devins & Shnek, 2000) to explain variations in wellness specifically related to participants' adaptation to diabetes. The theoretical model hypothesized that…

  6. Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

    Directory of Open Access Journals (Sweden)

    Min-Joo Kang

    Full Text Available A novel intrusion detection system (IDS using a deep neural network (DNN is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN, therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN bus.

  7. Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

    Science.gov (United States)

    Kang, Min-Joo; Kang, Je-Won

    2016-01-01

    A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN), therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN) bus.

  8. Implementation of Multipattern String Matching Accelerated with GPU for Intrusion Detection System

    Science.gov (United States)

    Nehemia, Rangga; Lim, Charles; Galinium, Maulahikmah; Rinaldi Widianto, Ahmad

    2017-04-01

    As Internet-related security threats continue to increase in terms of volume and sophistication, existing Intrusion Detection System is also being challenged to cope with the current Internet development. Multi Pattern String Matching algorithm accelerated with Graphical Processing Unit is being utilized to improve the packet scanning performance of the IDS. This paper implements a Multi Pattern String Matching algorithm, also called Parallel Failureless Aho Corasick accelerated with GPU to improve the performance of IDS. OpenCL library is used to allow the IDS to support various GPU, including popular GPU such as NVIDIA and AMD, used in our research. The experiment result shows that the application of Multi Pattern String Matching using GPU accelerated platform provides a speed up, by up to 141% in term of throughput compared to the previous research.

  9. Network Analysis of Reconnaissance and Intrusion of an Industrial Control System

    Science.gov (United States)

    2016-09-01

    COVERED (From - To) 07/2014–06/2016 4 . TITLE AND SUBTITLE Network Analysis of Reconnaissance and Intrusion of an Industrial Control System 5a... 0 / 0 10.10.14.0 Fa0/ 0 /1 10.10.15.1 Fa0/ 0 /2 10.10.16.1 2.1.4 Security Configuration 4 : Centralized Switch, IP Netmask Segregation, Separate VLANs...NA 2 4.00 2.83 0 NA NA Local master announcement 138 96 1.00 0.00 1 1.00 NA Microsoft LAN Manager (LANMAN) 139 365 2.61 0.93 4 2.50 1.00 Cisco

  10. Model of Acquisition, Transformation and Usage of Geographic Data Within an Informational System Adapted to Projecting Necessities

    OpenAIRE

    Nidelea Marinela; Barbaresso Mariana

    2011-01-01

    The necessity to attach complex information to these graphic entities as well as the possibility to make descriptive and graphic operation analysis on these items caused the GIS systems to take another direction from the CAD system simplifying the graphic representation of these entities and developing graphic processing functions, the realization of topologies and links between graphic elements and the descriptive information stored in complex relational data bases, with client/server archit...

  11. Context-aware local Intrusion Detection in SCADA systems : a testbed and two showcases

    NARCIS (Netherlands)

    Chromik, Justyna Joanna; Haverkort, Boudewijn R.H.M.; Remke, Anne Katharina Ingrid; Pilch, Carina; Brackmann, Pascal; Duhme, Christof; Everinghoff, Franziska; Giberlein, Artur; Teodorowicz, Thomas; Wieland, Julian

    2017-01-01

    This paper illustrates the use of a testbed that we have developed for context-aware local intrusion detection. This testbed is based on the co-simulation framework Mosaik and allows for the validation of local intrusion detection mechanisms at field stations in power distribution networks. For two

  12. Improved Information Retrieval Performance on SQL Database Using Data Adapter

    Science.gov (United States)

    Husni, M.; Djanali, S.; Ciptaningtyas, H. T.; Wicaksana, I. G. N. A.

    2018-02-01

    The NoSQL databases, short for Not Only SQL, are increasingly being used as the number of big data applications increases. Most systems still use relational databases (RDBs), but as the number of data increases each year, the system handles big data with NoSQL databases to analyze and access data more quickly. NoSQL emerged as a result of the exponential growth of the internet and the development of web applications. The query syntax in the NoSQL database differs from the SQL database, therefore requiring code changes in the application. Data adapter allow applications to not change their SQL query syntax. Data adapters provide methods that can synchronize SQL databases with NotSQL databases. In addition, the data adapter provides an interface which is application can access to run SQL queries. Hence, this research applied data adapter system to synchronize data between MySQL database and Apache HBase using direct access query approach, where system allows application to accept query while synchronization process in progress. From the test performed using data adapter, the results obtained that the data adapter can synchronize between SQL databases, MySQL, and NoSQL database, Apache HBase. This system spends the percentage of memory resources in the range of 40% to 60%, and the percentage of processor moving from 10% to 90%. In addition, from this system also obtained the performance of database NoSQL better than SQL database.

  13. Water System Adaptation To Hydrological Changes: Module 7, Adaptation Principles and Considerations

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  14. Adaptive Data Collection Mechanisms for Smart Monitoring of Distribution Grids

    DEFF Research Database (Denmark)

    Kemal, Mohammed Seifu; Olsen, Rasmus Løvenstein

    2016-01-01

    units. For electric distribution systems, Information from Smart Meters can be utilized to monitor and control the state of the grid. Hence, it is indeed inherent that data from Smart Meters should be collected in a resilient, reliable, secure and timely manner fulfilling all the communication...... requirements and standards. This paper presents a proposal for smart data collection mechanisms to monitor electrical grids with adaptive smart metering infrastructures. A general overview of a platform is given for testing, evaluating and implementing mechanisms to adapt Smart Meter data aggregation. Three...... main aspects of adaptiveness of the system are studied, adaptiveness to smart metering application needs, adaptiveness to changing communication network dynamics and adaptiveness to security attacks. Execution of tests will be conducted in real field experimental set-up and in an advanced hardware...

  15. BLACK HOLE ATTACK IN AODV & FRIEND FEATURES UNIQUE EXTRACTION TO DESIGN DETECTION ENGINE FOR INTRUSION DETECTION SYSTEM IN MOBILE ADHOC NETWORK

    Directory of Open Access Journals (Sweden)

    HUSAIN SHAHNAWAZ

    2012-10-01

    Full Text Available Ad-hoc network is a collection of nodes that are capable to form dynamically a temporary network without the support of any centralized fixed infrastructure. Since there is no central controller to determine the reliable & secure communication paths in Mobile Adhoc Network, each node in the ad hoc network has to rely on each other in order to forward packets, thus highly cooperative nodes are required to ensure that the initiated data transmission process does not fail. In a mobile ad hoc network (MANET where security is a crucial issue and they are forced to rely on the neighbor node, trust plays an important role that could improve the number of successful data transmission. Larger the number of trusted nodes, higher successful data communication process rates could be expected. In this paper, Black Hole attack is applied in the network, statistics are collected to design intrusion detection engine for MANET Intrusion Detection System (IDS. Feature extraction and rule inductions are applied to find out the accuracy of detection engine by using support vector machine. In this paper True Positive generated by the detection engine is very high and this is a novel approach in the area of Mobile Adhoc Intrusion detection system.

  16. Vapor Intrusion

    Science.gov (United States)

    Vapor intrusion occurs when there is a migration of volatile chemicals from contaminated groundwater or soil into an overlying building. Volatile chemicals can emit vapors that may migrate through subsurface soils and into indoor air spaces.

  17. Adapting bioinformatics curricula for big data

    Science.gov (United States)

    Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S.

    2016-01-01

    Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. PMID:25829469

  18. An immunological approach to intrusion detection

    OpenAIRE

    Watkins, A.

    2000-01-01

    This paper presents an examination of intrusion detection schemes. It discusses\\ud traditional views of intrusion detection, and examines the more novel, but perhaps more\\ud effective, approach to intrusion detection as modeled on the human immune system. The\\ud discussion looks at some of the implications raised by intrusion detection research for\\ud information security in general.

  19. Nanosatellite Launch Adapter System (NLAS)

    Science.gov (United States)

    Yost, Bruce D.; Hines, John W.; Agasid, Elwood F.; Buckley, Steven J.

    2010-01-01

    The utility of small spacecraft based on the University cubesat standard is becoming evident as more and more agencies and organizations are launching or planning to include nanosatellites in their mission portfolios. Cubesats are typically launched as secondary spacecraft in enclosed, containerized deployers such as the CalPoly Poly Picosat Orbital Deployer (P-POD) system. The P-POD allows for ease of integration and significantly reduces the risk exposure to the primary spacecraft and mission. NASA/ARC and the Operationally Responsive Space office are collaborating to develop a Nanosatellite Launch Adapter System (NLAS), which can accommodate multiple cubesat or cubesat-derived spacecraft on a single launch vehicle. NLAS is composed of the adapter structure, P-POD or similar spacecraft dispensers, and a sequencer/deployer system. This paper describes the NLAS system and it s future capabilities, and also provides status on the system s development and potential first use in space.

  20. A synthetic study on constaining a 2D density-dependent saltwater intrusion model using electrical imaging data

    DEFF Research Database (Denmark)

    Antonsson, Arni Valur; Nguyen, Frederic; Engesgaard, Peter Knudegaard

    different hydrological conditions. The results of this synthetic study demonstrated some of the (potential) benefits of applying the electrical imaging data for calibration of seawater intrusion models. Furthermore, it also shows some of the limits this method has as well as the associated uncertainties....... Compared to conventional methods, which only give (few) point information, electrical images can give data over large spatial distances but that can be of great value for groundwater modeling purposes. The aim of this study is to investigate in a synthetic way, the applicability of using electrical images....... This study was conducted as a part of the European project ALERT (GOCE-CT-2004-505329)....

  1. Adaptive dynamic capacity allocation scheme for voice and data transmission

    Science.gov (United States)

    Yu, Yonglin; Wang, Gang; Lei, Daocheng; Ma, Runnian

    2011-12-01

    Based on the theory of adaptive modulation, the compressed format is introduced in voice and data transmission, and a novel adaptive dynamic capability allocation algorithm is presented. In the given transmission system model, according to the channel state information (CSI) provided by channel estimating, the transmitter can adaptively select the modulation model, and shrink the voice symbol duration to improve the data throughput of data transmission. Simulation results shows that the novel algorithm can effectively evaluate the percentage occupation of data bit in one fame, and improve the data throughput.

  2. Adaptive fuzzy system for 3-D vision

    Science.gov (United States)

    Mitra, Sunanda

    1993-01-01

    An adaptive fuzzy system using the concept of the Adaptive Resonance Theory (ART) type neural network architecture and incorporating fuzzy c-means (FCM) system equations for reclassification of cluster centers was developed. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a control structure similar to that found in the Adaptive Resonance Theory (ART-1) network to identify the cluster centers initially. The initial classification of an input takes place in a two stage process; a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from Fuzzy c-Means (FCM) system equations for the centroids and the membership values. The operational characteristics of AFLC and the critical parameters involved in its operation are discussed. The performance of the AFLC algorithm is presented through application of the algorithm to the Anderson Iris data, and laser-luminescent fingerprint image data. The AFLC algorithm successfully classifies features extracted from real data, discrete or continuous, indicating the potential strength of this new clustering algorithm in analyzing complex data sets. The hybrid neuro-fuzzy AFLC algorithm will enhance analysis of a number of difficult recognition and control problems involved with Tethered Satellite Systems and on-orbit space shuttle attitude controller.

  3. Thunder - adaptive avalanche airbag system

    OpenAIRE

    Chen, Kan

    2017-01-01

    Skiing plays an important role in outdoor activities. It allows us to regain control of our body, makes us feel alive. However, in some cases, skiing comes with great risk. Avalanche is the worth thing a skier would like to encounter. Thunder is an adaptive avalanche airbag system. Usually, an avalanche airbag product can help you float on the snow in an avalanche circumstance. Thunder are more focusing on the human behavior, making this avalanche airbag system not only an effective safety eq...

  4. Adaptive, dynamic, and resilient systems

    CERN Document Server

    Suri, Niranjan

    2015-01-01

    As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.The book presents the insights of a different group of international experts in each chapter. Reporting on r

  5. Electrical Resistivity Imaging of Seawater Intrusion into the Monterey Bay Aquifer System.

    Science.gov (United States)

    Pidlisecky, A; Moran, T; Hansen, B; Knight, R

    2016-03-01

    We use electrical resistivity tomography to obtain a 6.8-km electrical resistivity image to a depth of approximately 150 m.b.s.l. along the coast of Monterey Bay. The resulting image is used to determine the subsurface distribution of saltwater- and freshwater-saturated sediments and the geologic controls on fluid distributions in the region. Data acquisition took place over two field seasons in 2011 and 2012. To maximize our ability to image both vertical and horizontal variations in the subsurface, a combination of dipole-dipole, Wenner, Wenner-gamma, and gradient measurements were made, resulting in a large final dataset of approximately 139,000 data points. The resulting resistivity section extends to a depth of 150 m.b.s.l., and is used, in conjunction with the gamma logs from four coastal monitoring wells to identify four dominant lithologic units. From these data, we are able to infer the existence of a contiguous clay layer in the southern portion of our transect, which prevents downward migration of the saltwater observed in the upper 25 m of the subsurface to the underlying freshwater aquifer. The saltwater and brackish water in the northern portion of the transect introduce the potential for seawater intrusion into the hydraulically connected freshwater aquifer to the south, not just from the ocean, but also laterally from north to south. © 2015, National Ground Water Association.

  6. ImmuneDB: a system for the analysis and exploration of high-throughput adaptive immune receptor sequencing data.

    Science.gov (United States)

    Rosenfeld, Aaron M; Meng, Wenzhao; Luning Prak, Eline T; Hershberg, Uri

    2017-01-15

    As high-throughput sequencing of B cells becomes more common, the need for tools to analyze the large quantity of data also increases. This article introduces ImmuneDB, a system for analyzing vast amounts of heavy chain variable region sequences and exploring the resulting data. It can take as input raw FASTA/FASTQ data, identify genes, determine clones, construct lineages, as well as provide information such as selection pressure and mutation analysis. It uses an industry leading database, MySQL, to provide fast analysis and avoid the complexities of using error prone flat-files. ImmuneDB is freely available at http://immunedb.comA demo of the ImmuneDB web interface is available at: http://immunedb.com/demo CONTACT: Uh25@drexel.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  7. Financial markets as adaptive systems

    Science.gov (United States)

    Potters, M.; Cont, R.; Bouchaud, J.-P.

    1998-02-01

    We show, by studying in detail the market prices of options on liquid markets, that the market has empirically corrected the simple, but inadequate Black-Scholes formula to account for two important statistical features of asset fluctuations: "fat tails" and correlations in the scale of fluctuations. These aspects, although not included in the pricing models, are very precisely reflected in the price fixed by the market as a whole. Financial markets thus behave as rather efficient adaptive systems.

  8. Seawater intrusion mapping using electrical resistivity tomography and hydrochemical data. An application in the coastal area of eastern Thermaikos Gulf, Greece

    Energy Technology Data Exchange (ETDEWEB)

    Kazakis, N., E-mail: kazanera@yahoo.com [Aristotle University of Thessaloniki, Department of Geology, Lab. of Engineering Geology & Hydrogeology, 54124 Thessaloniki (Greece); Pavlou, A. [Aristotle University of Thessaloniki, Department of Geology, Lab. of Engineering Geology & Hydrogeology, 54124 Thessaloniki (Greece); Vargemezis, G. [Aristotle University of Thessaloniki, Department of Geology, Lab. of Applied Geophysics, 54124 Thessaloniki (Greece); Voudouris, K.S.; Soulios, G. [Aristotle University of Thessaloniki, Department of Geology, Lab. of Engineering Geology & Hydrogeology, 54124 Thessaloniki (Greece); Pliakas, F. [Democritus University of Thrace, Department of Civil Engineering, Xanthi 67100 (Greece); Tsokas, G. [Aristotle University of Thessaloniki, Department of Geology, Lab. of Applied Geophysics, 54124 Thessaloniki (Greece)

    2016-02-01

    The aim of this study was to determine the extent and geometrical characteristics of seawater intrusion in the coastal aquifer of the eastern Thermaikos Gulf, Greece. Hydrochemical data and geoelectrical measurements were combined and supplemented to determine the hydrochemical regime of the study site in regard to seawater phenomena. Chemical analysis of groundwater was performed in 126 boreholes and fifteen electrical resistivity tomographies (ERT) were measured, whereas in two sites the ERT measurements were repeated following the wet season. The Cl{sup −} concentrations recorded reached 2240 mg/L indicating seawater intrusion which was also verified by ionic ratios. The ionic ratios were overlapped and a seawater intrusion map (SWIM) was produced. A significant part of the coastal aquifer (up to 150 km{sup 2}) is influenced by seawater intrusion. The areas with the most intensive salinization are located between Nea Kallikratia–Epanomi and Aggelochori–Peraia. According to the ERTs, in the influenced areas the salinization of the aquifer exceeds 1 km toward the mainland and its depth reaches 200 m. In the area surrounding Thessaloniki airport, the ERTs revealed salinization of the upper aquifer to depths of up to 40 m, whereas the lower aquifer is uninfluenced. This abnormal distribution of seawater intrusion demonstrates the value of geoelectrical methods in the study of seawater intrusion especially in areas with limited available hydrochemical data. - Highlights: • ERTs determined the geometrical characteristics of the saline aquifer. • An abnormal distribution of seawater intrusion was recorded. • Four ionic ratios overlapped and a seawater intrusion map was produced. • Cl{sup −} concentrations increased significantly from 2005 to 2010 by up to 1800 mg/L.

  9. Seawater intrusion mapping using electrical resistivity tomography and hydrochemical data. An application in the coastal area of eastern Thermaikos Gulf, Greece

    International Nuclear Information System (INIS)

    Kazakis, N.; Pavlou, A.; Vargemezis, G.; Voudouris, K.S.; Soulios, G.; Pliakas, F.; Tsokas, G.

    2016-01-01

    The aim of this study was to determine the extent and geometrical characteristics of seawater intrusion in the coastal aquifer of the eastern Thermaikos Gulf, Greece. Hydrochemical data and geoelectrical measurements were combined and supplemented to determine the hydrochemical regime of the study site in regard to seawater phenomena. Chemical analysis of groundwater was performed in 126 boreholes and fifteen electrical resistivity tomographies (ERT) were measured, whereas in two sites the ERT measurements were repeated following the wet season. The Cl − concentrations recorded reached 2240 mg/L indicating seawater intrusion which was also verified by ionic ratios. The ionic ratios were overlapped and a seawater intrusion map (SWIM) was produced. A significant part of the coastal aquifer (up to 150 km 2 ) is influenced by seawater intrusion. The areas with the most intensive salinization are located between Nea Kallikratia–Epanomi and Aggelochori–Peraia. According to the ERTs, in the influenced areas the salinization of the aquifer exceeds 1 km toward the mainland and its depth reaches 200 m. In the area surrounding Thessaloniki airport, the ERTs revealed salinization of the upper aquifer to depths of up to 40 m, whereas the lower aquifer is uninfluenced. This abnormal distribution of seawater intrusion demonstrates the value of geoelectrical methods in the study of seawater intrusion especially in areas with limited available hydrochemical data. - Highlights: • ERTs determined the geometrical characteristics of the saline aquifer. • An abnormal distribution of seawater intrusion was recorded. • Four ionic ratios overlapped and a seawater intrusion map was produced. • Cl − concentrations increased significantly from 2005 to 2010 by up to 1800 mg/L.

  10. Fuzzy Based Advanced Hybrid Intrusion Detection System to Detect Malicious Nodes in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Rupinder Singh

    2017-01-01

    Full Text Available In this paper, an Advanced Hybrid Intrusion Detection System (AHIDS that automatically detects the WSNs attacks is proposed. AHIDS makes use of cluster-based architecture with enhanced LEACH protocol that intends to reduce the level of energy consumption by the sensor nodes. AHIDS uses anomaly detection and misuse detection based on fuzzy rule sets along with the Multilayer Perceptron Neural Network. The Feed Forward Neural Network along with the Backpropagation Neural Network are utilized to integrate the detection results and indicate the different types of attackers (i.e., Sybil attack, wormhole attack, and hello flood attack. For detection of Sybil attack, Advanced Sybil Attack Detection Algorithm is developed while the detection of wormhole attack is done by Wormhole Resistant Hybrid Technique. The detection of hello flood attack is done by using signal strength and distance. An experimental analysis is carried out in a set of nodes; 13.33% of the nodes are determined as misbehaving nodes, which classified attackers along with a detection rate of the true positive rate and false positive rate. Sybil attack is detected at a rate of 99,40%; hello flood attack has a detection rate of 98, 20%; and wormhole attack has a detection rate of 99, 20%.

  11. A Process Engineering Approach to the Development and Integration of Intrusion Detection Techniques

    National Research Council Canada - National Science Library

    Ye, Nong

    2001-01-01

    ...) investigate system-level intrusion detection techniques for the fusion and correlation of local information about intrusions, based on the integration infrastructure for intrusion detection; and (3...

  12. A Process Engineering Approach to the Development and Integration of Intrusion Detection Techniques

    National Research Council Canada - National Science Library

    Ye, Nong

    2002-01-01

    ...) investigate system-level intrusion detection techniques for the fusion and correlation of local information about intrusions, based on the integration infrastructure for intrusion detection; and (3...

  13. AdaBoost-based algorithm for network intrusion detection.

    Science.gov (United States)

    Hu, Weiming; Hu, Wei; Maybank, Steve

    2008-04-01

    Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

  14. Computerized adaptive testing item selection in computerized adaptive learning systems

    NARCIS (Netherlands)

    Eggen, Theodorus Johannes Hendrikus Maria; Eggen, T.J.H.M.; Veldkamp, B.P.

    2012-01-01

    Item selection methods traditionally developed for computerized adaptive testing (CAT) are explored for their usefulness in item-based computerized adaptive learning (CAL) systems. While in CAT Fisher information-based selection is optimal, for recovering learning populations in CAL systems item

  15. Information Assurance Intrusion Detection Sensor Database Design: Lessons Learned

    National Research Council Canada - National Science Library

    Spink, Brian

    2001-01-01

    Current architectural trends in information assurance for the DOD focuses on the fusion and correlation of large volumes of data collected across several intrusion detection systems and boundary devices...

  16. Zero Trust Intrusion Containment for Telemedicine

    National Research Council Canada - National Science Library

    Sood, Arun

    2002-01-01

    .... Our objective is the design and analysis of 'zero-trust' Intrusion Tolerant Systems. These are systems built under the extreme assumption that all intrusion detection techniques will eventually fail...

  17. Computer Network Equipment for Intrusion Detection Research

    National Research Council Canada - National Science Library

    Ye, Nong

    2000-01-01

    .... To test the process model, the system-level intrusion detection techniques and the working prototype of the intrusion detection system, a set of computer and network equipment has been purchased...

  18. Interaction between magma intrusion and flank dynamics at Mt. Etna in 2008, imaged by integrated dense GPS and DInSAR data

    Science.gov (United States)

    Bonforte, Alessandro; Guglielmino, Francesco; Puglisi, Giuseppe

    2013-08-01

    Global positioning system (GPS) and differential interferometric synthetic aperture radar (DInSAR) data, collected from July 2007 to July 2008 on Mt. Etna, are analyzed to define the dynamics preceding and accompanying the onset of the eruption on 13 May 2008. Short- and long-term comparisons have been made on both GPS and radar data, covering similar time windows. Thanks to the availability of three GPS surveys the year before the eruption onset, an increase in the seaward movement of the NE flank of the volcano has been detected in the few months before the dike intrusion. The GPS ground deformation pattern also shows a slight inflation centered on the western side of the volcano in the preeruptive long-term comparison (from July 2007 to May 2008). The GPS has been integrated with DInSAR data by the SISTEM approach, to take advantage of the different methodologies and provide high spatial sampling of the 3-D ground displacement pattern. We inverted the SISTEM results to model the pressure source causing the observed preeruptive inflation. The subsequent emplacement of the eruptive dike was imaged by two GPS surveys carried out on a dense network over the uppermost part of the volcano on 6 and 13 May, i.e., a few days before and a few hours after the beginning of the eruption. We inverted this comparison to define the position, geometry, and kinematics of the dike. The dike intrusion was also imaged by DInSAR data with temporal baselines of 2-3 months, which confirm strong displacements localized on the summit area, rapidly decreasing toward the middle flanks of the volcano, as detected by very short-term GPS data; furthermore, the comparison between DInSAR and GPS data highlighted the presence of a depressurizing source localized beneath the upper southwestern area, acting just after the dike intrusion. Finally, the long-period (1 year) GPS and DInSAR data were integrated by SISTEM to finely depict the 3-D ground deformation pattern with the highest spatial

  19. Statistical Inference for Data Adaptive Target Parameters.

    Science.gov (United States)

    Hubbard, Alan E; Kherad-Pajouh, Sara; van der Laan, Mark J

    2016-05-01

    Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples, and use this partitioning to define V splits in an estimation sample (one of the V subsamples) and corresponding complementary parameter-generating sample. For each of the V parameter-generating samples, we apply an algorithm that maps the sample to a statistical target parameter. We define our sample-split data adaptive statistical target parameter as the average of these V-sample specific target parameters. We present an estimator (and corresponding central limit theorem) of this type of data adaptive target parameter. This general methodology for generating data adaptive target parameters is demonstrated with a number of practical examples that highlight new opportunities for statistical learning from data. This new framework provides a rigorous statistical methodology for both exploratory and confirmatory analysis within the same data. Given that more research is becoming "data-driven", the theory developed within this paper provides a new impetus for a greater involvement of statistical inference into problems that are being increasingly addressed by clever, yet ad hoc pattern finding methods. To suggest such potential, and to verify the predictions of the theory, extensive simulation studies, along with a data analysis based on adaptively determined intervention rules are shown and give insight into how to structure such an approach. The results show that the data adaptive target parameter approach provides a general framework and resulting methodology for data-driven science.

  20. Processing and Linguistics Properties of Adaptable Systems

    Directory of Open Access Journals (Sweden)

    Dumitru TODOROI

    2006-01-01

    Full Text Available Continuation and development of the research in Adaptable Programming Initialization [Tod-05.1,2,3] is presented. As continuation of [Tod-05.2,3] in this paper metalinguistic tools used in the process of introduction of new constructions (data, operations, instructions and controls are developed. The generalization schemes of evaluation of adaptable languages and systems are discussed. These results analogically with [Tod-05.2,3] are obtained by the team, composed from the researchers D. Todoroi [Tod-05.4], Z. Todoroi [ZTod-05], and D. Micusa [Mic-03]. Presented results will be included in the book [Tod-06].

  1. A novel interacting multiple model based network intrusion detection scheme

    Science.gov (United States)

    Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry

    2006-04-01

    In today's information age, information and network security are of primary importance to any organization. Network intrusion is a serious threat to security of computers and data networks. In internet protocol (IP) based network, intrusions originate in different kinds of packets/messages contained in the open system interconnection (OSI) layer 3 or higher layers. Network intrusion detection and prevention systems observe the layer 3 packets (or layer 4 to 7 messages) to screen for intrusions and security threats. Signature based methods use a pre-existing database that document intrusion patterns as perceived in the layer 3 to 7 protocol traffics and match the incoming traffic for potential intrusion attacks. Alternately, network traffic data can be modeled and any huge anomaly from the established traffic pattern can be detected as network intrusion. The latter method, also known as anomaly based detection is gaining popularity for its versatility in learning new patterns and discovering new attacks. It is apparent that for a reliable performance, an accurate model of the network data needs to be established. In this paper, we illustrate using collected data that network traffic is seldom stationary. We propose the use of multiple models to accurately represent the traffic data. The improvement in reliability of the proposed model is verified by measuring the detection and false alarm rates on several datasets.

  2. Towards Adaptive Spoken Dialog Systems

    CERN Document Server

    Schmitt, Alexander

    2013-01-01

    In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and  accurate use.  Beginning with the foundations of machine learning and pattern recognition, this monograph examines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make use of statistical methods based on acoustic, linguistic and contextual features to examine the relationship between the interaction flow and the occurrence of emotions using non-acted  recordings several thousand real users from commercial and non-commercial SDS. Additionally, the authors present novel statistical methods that spot problems within a dialog based on interaction patterns. The approaches enable future SDS to offer m...

  3. Self-adaptive change detection in streaming data with non-stationary distribution

    KAUST Repository

    Zhang, Xiangliang

    2010-01-01

    Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non-stationary distribution helps to alarm the anomalies, to clean the noises, and to report the new patterns. In this paper, we employ a novel approach for detecting changes in streaming data with the purpose of improving the quality of modeling the data streams. Through observing the outliers, this approach of change detection uses a weighted standard deviation to monitor the evolution of the distribution of data streams. A cumulative statistical test, Page-Hinkley, is employed to collect the evidence of changes in distribution. The parameter used for reporting the changes is self-adaptively adjusted according to the distribution of data streams, rather than set by a fixed empirical value. The self-adaptability of the novel approach enhances the effectiveness of modeling data streams by timely catching the changes of distributions. We validated the approach on an online clustering framework with a benchmark KDDcup 1999 intrusion detection data set as well as with a real-world grid data set. The validation results demonstrate its better performance on achieving higher accuracy and lower percentage of outliers comparing to the other change detection approaches. © 2010 Springer-Verlag.

  4. APPROACH TO ADAPTIVE LEARNING MANAGEMENT SYSTEM DESIGN

    Directory of Open Access Journals (Sweden)

    Vitaly A. Gaevoy

    2014-01-01

    Full Text Available In this paper, we describe how to increase the learning management systems effi ciency by using an adaptive approach. In our work we try and summarize the existing systems; the adaptability absence problem is discovered, programming and architectural adaptive learning management system designing approach is offered. 

  5. Resident Load Influence Analysis Method for Price Based on Non-intrusive Load Monitoring and Decomposition Data

    Science.gov (United States)

    Jiang, Wenqian; Zeng, Bo; Yang, Zhou; Li, Gang

    2018-01-01

    In the non-invasive load monitoring mode, the load decomposition can reflect the running state of each load, which will help the user reduce unnecessary energy costs. With the demand side management measures of time of using price, a resident load influence analysis method for time of using price (TOU) based on non-intrusive load monitoring data are proposed in the paper. Relying on the current signal of the resident load classification, the user equipment type, and different time series of self-elasticity and cross-elasticity of the situation could be obtained. Through the actual household load data test with the impact of TOU, part of the equipment will be transferred to the working hours, and users in the peak price of electricity has been reduced, and in the electricity at the time of the increase Electrical equipment, with a certain regularity.

  6. Proposed Network Intrusion Detection System ‎In Cloud Environment Based on Back ‎Propagation Neural Network

    Directory of Open Access Journals (Sweden)

    Shawq Malik Mehibs

    2017-12-01

    Full Text Available Cloud computing is distributed architecture, providing computing facilities and storage resource as a service over the internet. This low-cost service fulfills the basic requirements of users. Because of the open nature and services introduced by cloud computing intruders impersonate legitimate users and misuse cloud resource and services. To detect intruders and suspicious activities in and around the cloud computing environment, intrusion detection system used to discover the illegitimate users and suspicious action by monitors different user activities on the network .this work proposed based back propagation artificial neural network to construct t network intrusion detection in the cloud environment. The proposed module evaluated with kdd99 dataset the experimental results shows promising approach to detect attack with high detection rate and low false alarm rate

  7. Anomaly based intrusion detection for a biometric identification system using neural networks

    CSIR Research Space (South Africa)

    Mgabile, T

    2012-10-01

    Full Text Available detection technique that analyses the fingerprint biometric network traffic for evidence of intrusion. The neural network algorithm that imitates the way a human brain works is used in this study to classify normal traffic and learn the correct traffic...

  8. Diagnosing and Reconstructing Real-World Hydroclimatic Dynamics from Time Sequenced Data: The Case of Saltwater Intrusion into Coastal Wetlands in Everglades National Park

    Science.gov (United States)

    Huffaker, R.; Munoz-Carpena, R.

    2016-12-01

    There are increasing calls to audit decision-support models used for environmental policy to ensure that they correspond with the reality facing policy makers. Modelers can establish correspondence by providing empirical evidence of real-world dynamic behavior that their models skillfully simulate. We present a pre-modeling diagnostic framework—based on nonlinear dynamic analysis—for detecting and reconstructing real-world environmental dynamics from observed time-sequenced data. Phenomenological (data-driven) modeling—based on machine learning regression techniques—extracts a set of ordinary differential equations governing empirically-diagnosed system dynamics from a single time series, or from multiple time series on causally-interacting variables. We apply the framework to investigate saltwater intrusion into coastal wetlands in Everglades National Park, Florida, USA. We test the following hypotheses posed in the literature linking regional hydrologic variables with global climatic teleconnections: (1) Sea level in Florida Bay drives well level and well salinity in the coastal Everglades; (2) Atlantic Multidecadal Oscillation (AMO) drives sea level, well level and well salinity; and (3) AMO and (El Niño Southern Oscillation) ENSO bi-causally interact. The thinking is that salt water intrusion links ocean-surface salinity with salinity of inland water sources, and sea level with inland water; that AMO and ENSO share a teleconnective relationship (perhaps through the atmosphere); and that AMO and ENSO both influence inland precipitation and thus well levels. Our results support these hypotheses, and we successfully construct a parsimonious phenomenological model that reproduces diagnosed nonlinear dynamics and system interactions. We propose that reconstructed data dynamics be used, along with other expert information, as a rigorous benchmark to guide specification and testing of hydrologic decision support models corresponding with real-world behavior.

  9. Sampled-Data Kalman Filtering and Multiple Model Adaptive Estimation for Infinite-Dimensional Continuous-Time Systems

    Science.gov (United States)

    2007-03-01

    grain particles suspended in a fluid and Norbert Wiener developed the mathematical foundation for this type of random motion [209, 21]. 3-38 Definition...Technology and John Wiley & Sons, Inc., 1949. 209. Wiener , Norbert , et al. Differential Space, Quantum Systems, and Prediction. Cambridge, Massachusetts...space of bounded linear transformations . . . . . . . . 3-6 xvii Symbol Page b(t) Brownian motion (or Wiener ) process . . . . . . . . . 2-10 C([a, b

  10. Applying a non-intrusive energy-management system to economic dispatch for a cogeneration system and power utility

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Hsueh-Hsien [Dept. of Electrical Engineering, Chung Yuan Christian University, Taoyuan (China); Dept. of Electronic Engineering, Jin Wen University of Science and Technology, Taipei (China); Yang, Hong-Tzer [Dept. of Electrical Engineering, National Cheng Kung University, Tainan (China)

    2009-11-15

    Non-intrusive energy-management (NIEM) techniques are based on energy signatures. While such approaches lack transient energy signatures, the reliability and accuracy of recognition results cannot be determined. By using neural networks (NNs) in combination with turn-on transient energy analysis, this study attempts to identify load demands and improve recognition accuracy of NIEM results. Case studies are presented that apply various methods to compare training algorithms and classifiers in terms of artificial neural networks (ANN) due to various factors that determine whether a network is being used for pattern recognition. Additionally, in combination with electromagnetic transient program (EMTP) simulations, calculating the turn-on transient energy facilitate load can lead to identification and a significant improvement in the accuracy of NIEM results. Analysis results indicate that an NIEM system can effectively manage energy demands within economic dispatch for a cogeneration system and power utility. Additionally, a new method based on genetic algorithms (GAs) is used to develop a novel operational strategy of economic dispatch for a cogeneration system in a regulated market and approach the global optimum with typical environmental constraints for a cogeneration plant. Economic dispatch results indicate that the NIEM system based on energy demands can estimate accurately the energy contribution from the cogeneration system and power utility, and further reduce air pollution. Moreover, applying the NIEM system for economic dispatch can markedly reduce computational time and power costs. (author)

  11. Multi-rate cubature Kalman filter based data fusion method with residual compensation to adapt to sampling rate discrepancy in attitude measurement system.

    Science.gov (United States)

    Guo, Xiaoting; Sun, Changku; Wang, Peng

    2017-08-01

    This paper investigates the multi-rate inertial and vision data fusion problem in nonlinear attitude measurement systems, where the sampling rate of the inertial sensor is much faster than that of the vision sensor. To fully exploit the high frequency inertial data and obtain favorable fusion results, a multi-rate CKF (Cubature Kalman Filter) algorithm with estimated residual compensation is proposed in order to adapt to the problem of sampling rate discrepancy. During inter-sampling of slow observation data, observation noise can be regarded as infinite. The Kalman gain is unknown and approaches zero. The residual is also unknown. Therefore, the filter estimated state cannot be compensated. To obtain compensation at these moments, state error and residual formulas are modified when compared with the observation data available moments. Self-propagation equation of the state error is established to propagate the quantity from the moments with observation to the moments without observation. Besides, a multiplicative adjustment factor is introduced as Kalman gain, which acts on the residual. Then the filter estimated state can be compensated even when there are no visual observation data. The proposed method is tested and verified in a practical setup. Compared with multi-rate CKF without residual compensation and single-rate CKF, a significant improvement is obtained on attitude measurement by using the proposed multi-rate CKF with inter-sampling residual compensation. The experiment results with superior precision and reliability show the effectiveness of the proposed method.

  12. Semantic models for adaptive interactive systems

    CERN Document Server

    Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

    2013-01-01

    Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

  13. The implementation of two stages clustering (k-means clustering and adaptive neuro fuzzy inference system) for prediction of medicine need based on medical data

    Science.gov (United States)

    Husein, A. M.; Harahap, M.; Aisyah, S.; Purba, W.; Muhazir, A.

    2018-03-01

    Medication planning aim to get types, amount of medicine according to needs, and avoid the emptiness medicine based on patterns of disease. In making the medicine planning is still rely on ability and leadership experience, this is due to take a long time, skill, difficult to obtain a definite disease data, need a good record keeping and reporting, and the dependence of the budget resulted in planning is not going well, and lead to frequent lack and excess of medicines. In this research, we propose Adaptive Neuro Fuzzy Inference System (ANFIS) method to predict medication needs in 2016 and 2017 based on medical data in 2015 and 2016 from two source of hospital. The framework of analysis using two approaches. The first phase is implementing ANFIS to a data source, while the second approach we keep using ANFIS, but after the process of clustering from K-Means algorithm, both approaches are calculated values of Root Mean Square Error (RMSE) for training and testing. From the testing result, the proposed method with better prediction rates based on the evaluation analysis of quantitative and qualitative compared with existing systems, however the implementation of K-Means Algorithm against ANFIS have an effect on the timing of the training process and provide a classification accuracy significantly better without clustering.

  14. Data Requirements for Developing Adaptations to Climate Variability and Change

    International Nuclear Information System (INIS)

    Basher, Reid E.

    1999-01-01

    An extensive foundation of high quality data and information on the climate and on the biological, environmental and social systems affected by climate is required in order to understand the climate impact processes involved, to develop new adaptation practices, and to subsequently implement these practices. Experience of the impacts of current and past variability of climate and sea level is a prime source of information. Many practices are in use to reduce climate impacts, for example in engineering design, agricultural risk management and climate prediction services, though their roles as adaptations to climate change are not widely appreciated. While there are good data sets on some factors and in some regions, in many cases the databases are inadequate and there are few data sets on adaptation-specific quantities such as vulnerability, resilience and adaptation effectiveness. Current international action under the United Nations Framework Convention on Climate Change (UNFCCC) pays little attention to adaptation and its information requirements. Furthermore there are trends toward reduced data gathering and to restrictions on access to data sets, especially arising from cost and commercialisation pressures. To effectively respond to the changes in climate that are now inevitable, governments will need to more clearly identify adaptation as a central feature of climate change policy and make a renewed shared commitment to collecting and freely exchanging the necessary data. 12 refs

  15. Adaptive Embedded Digital System for Plasma Diagnostics

    Science.gov (United States)

    González, Angel; Rodríguez, Othoniel; Mangual, Osvaldo; Ponce, Eduardo; Vélez, Xavier

    2014-05-01

    An Adaptive Embedded Digital System to perform plasma diagnostics using electrostatic probes was developed at the Plasma Engineering Laboratory at Polytechnic University of Puerto Rico. The system will replace the existing instrumentation at the Laboratory, using reconfigurable hardware to minimize the equipment and software needed to perform diagnostics. The adaptability of the design resides on the possibility of replacing the computational algorithm on the fly, allowing to use the same hardware for different probes. The system was prototyped using Very High Speed Integrated Circuits Hardware Description Language (VHDL) into an Field Programmable Gate Array (FPGA) board. The design of the Embedded Digital System includes a Zero Phase Digital Filter, a Derivative Unit, and a Computational Unit designed using the VHDL-2008 Support Library. The prototype is able to compute the Plasma Electron Temperature and Density from a Single Langmuir probe. The system was tested using real data previously acquired from a single Langmuir probe. The plasma parameters obtained from the embedded system were compared with results computed using matlab yielding excellent matching. The new embedded system operates on 4096 samples versus 500 on the previous system, and completes its computations in 26 milliseconds compared with about 15 seconds on the previous system.

  16. Environment Adaptive Lighting Systems for Smart Homes

    Directory of Open Access Journals (Sweden)

    Cem Mehmet Catalbas

    2017-09-01

    Full Text Available In this work, an application of adaptive lighting system is proposed for smart homes. In this paper, it is suggested that, an intelligent lighting system with outdoor adaptation can be realized via a real fisheye image. During the implementation of the proposed method, the fuzzy c-means method, which is a commonly used data clustering method, has been used. The input image is divided into three different regions according to its brightness levels. Then, the RGB image is converted to CIE 1931 XYZ color space; and the obtained XYZ values are converted to x and y values. The parameters of x and y values are shown in CIE Chromaticity Diagram for different regions in the sky. Thereafter, the coordinate values are converted to Correlated Color Temperature by using two different formulas. Additionally, the conversion results are examined with respect to actual and estimated CCT values.

  17. Computational overlay metrology with adaptive data analytics

    Science.gov (United States)

    Schmitt-Weaver, Emil; Subramony, Venky; Ullah, Zakir; Matsunobu, Masazumi; Somasundaram, Ravin; Thomas, Joel; Zhang, Linmiao; Thul, Klaus; Bhattacharyya, Kaustuve; Goossens, Ronald; Lambregts, Cees; Tel, Wim; de Ruiter, Chris

    2017-03-01

    With photolithography as the fundamental patterning step in the modern nanofabrication process, every wafer within a semiconductor fab will pass through a lithographic apparatus multiple times. With more than 20,000 sensors producing more than 700GB of data per day across multiple subsystems, the combination of a light source and lithographic apparatus provide a massive amount of information for data analytics. This paper outlines how data analysis tools and techniques that extend insight into data that traditionally had been considered unmanageably large, known as adaptive analytics, can be used to show how data collected before the wafer is exposed can be used to detect small process dependent wafer-towafer changes in overlay.

  18. Intrusion Detection in Networked Control Systems: From System Knowledge to Network Security

    NARCIS (Netherlands)

    Caselli, M.

    2016-01-01

    “Networked control system‿ (NCS) is an umbrella term encompassing a broad variety of infrastructures such as industrial control systems (ICSs) and building automation systems (BASs). Nowadays, all these infrastructures play an important role in several aspects of our daily life, from managing

  19. Complex Environmental Data Modelling Using Adaptive General Regression Neural Networks

    Science.gov (United States)

    Kanevski, Mikhail

    2015-04-01

    The research deals with an adaptation and application of Adaptive General Regression Neural Networks (GRNN) to high dimensional environmental data. GRNN [1,2,3] are efficient modelling tools both for spatial and temporal data and are based on nonparametric kernel methods closely related to classical Nadaraya-Watson estimator. Adaptive GRNN, using anisotropic kernels, can be also applied for features selection tasks when working with high dimensional data [1,3]. In the present research Adaptive GRNN are used to study geospatial data predictability and relevant feature selection using both simulated and real data case studies. The original raw data were either three dimensional monthly precipitation data or monthly wind speeds embedded into 13 dimensional space constructed by geographical coordinates and geo-features calculated from digital elevation model. GRNN were applied in two different ways: 1) adaptive GRNN with the resulting list of features ordered according to their relevancy; and 2) adaptive GRNN applied to evaluate all possible models N [in case of wind fields N=(2^13 -1)=8191] and rank them according to the cross-validation error. In both cases training were carried out applying leave-one-out procedure. An important result of the study is that the set of the most relevant features depends on the month (strong seasonal effect) and year. The predictabilities of precipitation and wind field patterns, estimated using the cross-validation and testing errors of raw and shuffled data, were studied in detail. The results of both approaches were qualitatively and quantitatively compared. In conclusion, Adaptive GRNN with their ability to select features and efficient modelling of complex high dimensional data can be widely used in automatic/on-line mapping and as an integrated part of environmental decision support systems. 1. Kanevski M., Pozdnoukhov A., Timonin V. Machine Learning for Spatial Environmental Data. Theory, applications and software. EPFL Press

  20. Research on the technology of detecting the SQL injection attack and non-intrusive prevention in WEB system

    Science.gov (United States)

    Hu, Haibin

    2017-05-01

    Among numerous WEB security issues, SQL injection is the most notable and dangerous. In this study, characteristics and procedures of SQL injection are analyzed, and the method for detecting the SQL injection attack is illustrated. The defense resistance and remedy model of SQL injection attack is established from the perspective of non-intrusive SQL injection attack and defense. Moreover, the ability of resisting the SQL injection attack of the server has been comprehensively improved through the security strategies on operation system, IIS and database, etc.. Corresponding codes are realized. The method is well applied in the actual projects.

  1. Modeling Power Systems as Complex Adaptive Systems

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  2. Adapt

    Science.gov (United States)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  3. Saltwater intrusion in the surficial aquifer system of the Big Cypress Basin, southwest Florida, and a proposed plan for improved salinity monitoring

    Science.gov (United States)

    Prinos, Scott T.

    2013-01-01

    The installation of drainage canals, poorly cased wells, and water-supply withdrawals have led to saltwater intrusion in the primary water-use aquifers in southwest Florida. Increasing population and water use have exacerbated this problem. Installation of water-control structures, well-plugging projects, and regulation of water use have slowed saltwater intrusion, but the chloride concentration of samples from some of the monitoring wells in this area indicates that saltwater intrusion continues to occur. In addition, rising sea level could increase the rate and extent of saltwater intrusion. The existing saltwater intrusion monitoring network was examined and found to lack the necessary organization, spatial distribution, and design to properly evaluate saltwater intrusion. The most recent hydrogeologic framework of southwest Florida indicates that some wells may be open to multiple aquifers or have an incorrect aquifer designation. Some of the sampling methods being used could result in poor-quality data. Some older wells are badly corroded, obstructed, or damaged and may not yield useable samples. Saltwater in some of the canals is in close proximity to coastal well fields. In some instances, saltwater occasionally occurs upstream from coastal salinity control structures. These factors lead to an incomplete understanding of the extent and threat of saltwater intrusion in southwest Florida. A proposed plan to improve the saltwater intrusion monitoring network in the South Florida Water Management District’s Big Cypress Basin describes improvements in (1) network management, (2) quality assurance, (3) documentation, (4) training, and (5) data accessibility. The plan describes improvements to hydrostratigraphic and geospatial network coverage that can be accomplished using additional monitoring, surface geophysical surveys, and borehole geophysical logging. Sampling methods and improvements to monitoring well design are described in detail. Geochemical analyses

  4. Adaptive Analysis of Functional MRI Data

    International Nuclear Information System (INIS)

    Friman, Ola

    2003-01-01

    Functional Magnetic Resonance Imaging (fMRI) is a recently developed neuro-imaging technique with capacity to map neural activity with high spatial precision. To locate active brain areas, the method utilizes local blood oxygenation changes which are reflected as small intensity changes in a special type of MR images. The ability to non-invasively map brain functions provides new opportunities to unravel the mysteries and advance the understanding of the human brain, as well as to perform pre-surgical examinations in order to optimize surgical interventions. This dissertation introduces new approaches for the analysis of fMRI data. The detection of active brain areas is a challenging problem due to high noise levels and artifacts present in the data. A fundamental tool in the developed methods is Canonical Correlation Analysis (CCA). CCA is used in two novel ways. First as a method with the ability to fully exploit the spatio-temporal nature of fMRI data for detecting active brain areas. Established analysis approaches mainly focus on the temporal dimension of the data and they are for this reason commonly referred to as being mass-univariate. The new CCA detection method encompasses and generalizes the traditional mass-univariate methods and can in this terminology be viewed as a mass-multivariate approach. The concept of spatial basis functions is introduced as a spatial counterpart of the temporal basis functions already in use in fMRI analysis. The spatial basis functions implicitly perform an adaptive spatial filtering of the fMRI images, which significantly improves detection performance. It is also shown how prior information can be incorporated into the analysis by imposing constraints on the temporal and spatial models and a constrained version of CCA is devised to this end. A general Principal Component Analysis technique for generating and constraining temporal and spatial subspace models is proposed to be used in combination with the constrained CCA

  5. Enhancing Trust Management for Wireless Intrusion Detection via Traffic Sampling in the Era of Big Data

    DEFF Research Database (Denmark)

    Meng, Weizhi; Li, Wenjuan; Su, Chunhua

    2017-01-01

    Internet of Things (IoT) has been widely used in our daily life, which enables various objects to be interconnected for data exchange, including physical devices, vehicles, and other items embedded with network connectivity. Wireless sensor network (WSN) is a vital application of IoT, providing...... against insider attacks through implementing proper trustbased mechanisms. However, in the era of big data, sensors may generate excessive information and data, which could degrade the effectiveness of trust computation. In this paper, we focus on this challenge and propose a way of combining Bayesian...

  6. Visualization Tools for Adaptive Mesh Refinement Data

    Energy Technology Data Exchange (ETDEWEB)

    Weber, Gunther H.; Beckner, Vincent E.; Childs, Hank; Ligocki,Terry J.; Miller, Mark C.; Van Straalen, Brian; Bethel, E. Wes

    2007-05-09

    Adaptive Mesh Refinement (AMR) is a highly effective method for simulations that span a large range of spatiotemporal scales, such as astrophysical simulations that must accommodate ranges from interstellar to sub-planetary. Most mainstream visualization tools still lack support for AMR as a first class data type and AMR code teams use custom built applications for AMR visualization. The Department of Energy's (DOE's) Science Discovery through Advanced Computing (SciDAC) Visualization and Analytics Center for Enabling Technologies (VACET) is currently working on extending VisIt, which is an open source visualization tool that accommodates AMR as a first-class data type. These efforts will bridge the gap between general-purpose visualization applications and highly specialized AMR visual analysis applications. Here, we give an overview of the state of the art in AMR visualization research and tools and describe how VisIt currently handles AMR data.

  7. SHRIMP U-Pb zircon geochronology and thermal modeling of multilayer granitoid intrusions. Implications for the building and thermal evolution of the Central System batholith, Iberian Massif, Spain

    Science.gov (United States)

    Díaz Alvarado, Juan; Fernández, Carlos; Castro, Antonio; Moreno-Ventas, Ignacio

    2013-08-01

    This work shows the results of a U-Pb SHRIMP zircon geochronological study of the central part of the Gredos massif (Spanish Central System batholith). The studied batholith is composed of several granodiorite and monzogranite tabular bodies, around 1 km thick each, intruded into partially molten pelitic metasediments. Granodiorites and monzogranites, belonging to three distinct intrusive bodies, and samples of anatectic leucogranites have been selected for SHRIMP U-Pb zircon geochronology. Distinct age groups, separated by up to 20 Ma, have been distinguished in each sample. Important age differences have also been determined among the most representative age groups of the three analyzed granitoid bodies: 312.6 ± 2.8 Ma for the Circo de Gredos Bt-granodiorites (floor intrusive layer), 306.9 ± 1.5 Ma for the Barbellido-Plataforma granitoids (top intrusive layer) and 303.5 ± 2.8 Ma for Las Pozas Crd-monzogranites (middle intrusive layer). These age differences are interpreted in terms of sequential emplacement of the three intrusive bodies, contemporary with the Late Paleozoic D3 deformation phase. The anatectic leucogranites are coeval to slightly younger than the adjacent intrusive granodiorites and monzogranites (305.4 ± 1.6 Ma for Refugio del Rey leucogranites and 303 ± 2 Ma for migmatitic hornfelses). It is suggested that these anatectic magmas were generated in response to the thermal effects of granodiorite intrusions. Thermal modeling with COMSOL Multiphysics® reveals that sequential emplacement was able to keep the thermal conditions of the batholith around the temperature of zircon crystallization in granitic melts (around 750 °C) for several million of years, favoring the partial melting of host rocks and the existence of large magma chambers composed of crystal mush prone to be rejuvenated after new intrusions.

  8. Environment-Sensitive Intrusion Detection

    National Research Council Canada - National Science Library

    Giffin, Jonathan T; Dagon, David; Jha, Somesh; Lee, Wenke; Miller, Barton P

    2006-01-01

    .... We improve the effectiveness of such model-based intrusion detection systems by incorporating into the model knowledge of the environment in which the program runs, and by increasing the accuracy...

  9. Visual Cues for an Adaptive Expert System.

    Science.gov (United States)

    Miller, Helen B.

    NCR (National Cash Register) Corporation is pursuing opportunities to make their point of sale (POS) terminals easy to use and easy to learn. To approach the goal of making the technology invisible to the user, NCR has developed an adaptive expert prototype system for a department store POS operation. The structure for the adaptive system, the…

  10. Sulfide intrusion and detoxification in Zostera marina

    DEFF Research Database (Denmark)

    Hasler-Sheetal, Harald; Holmer, Marianne

    2014-01-01

    Sulfide intrusion in seagrasses represents a global threat to seagrasses. In contrast seegrasses grow in hostile sediments, where they are constantly exposed to sulfide intrusion. Little is known about the strategies to survive sulfide intrusion, if there are detoxification mechanisms and sulfur...... indicating a possible role of sulfide in the sulfur nutrition beside the detoxification function. Our results suggest different adaptations of Z. marina to reduced sediments and sulfide intrusion ranging from bacterial and chemical reoxidation of sulfide to sulfate to incorporation of sulfide into organic...

  11. Accumulo/Hadoop, MongoDB, and Elasticsearch Performance for Semi Structured Intrusion Detection (IDS) Data

    Science.gov (United States)

    2016-11-01

    costly solution. After examining available options, the open-source database PostgreSQL8 was chosen as a potential replacement. PostgreSQL offered...with sufficient confidence to move forward with our migration plan. Several years have passed since the successful migration to PostgreSQL ; data...volumes have continued to increase and it is again time to review options to replace PostgreSQL with a component that will allow easier and more cost

  12. Intelligent Multimodal Signal Adaptation System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Micro Analysis and Design (MA&D) is pleased to submit this proposal to design an Intelligent Multimodal Signal Adaptation System. This system will dynamically...

  13. Operator adaptation to changes in system reliability under adaptable automation.

    Science.gov (United States)

    Chavaillaz, Alain; Sauer, Juergen

    2017-09-01

    This experiment examined how operators coped with a change in system reliability between training and testing. Forty participants were trained for 3 h on a complex process control simulation modelling six levels of automation (LOA). In training, participants either experienced a high- (100%) or low-reliability system (50%). The impact of training experience on operator behaviour was examined during a 2.5 h testing session, in which participants either experienced a high- (100%) or low-reliability system (60%). The results showed that most operators did not often switch between LOA. Most chose an LOA that relieved them of most tasks but maintained their decision authority. Training experience did not have a strong impact on the outcome measures (e.g. performance, complacency). Low system reliability led to decreased performance and self-confidence. Furthermore, complacency was observed under high system reliability. Overall, the findings suggest benefits of adaptable automation because it accommodates different operator preferences for LOA. Practitioner Summary: The present research shows that operators can adapt to changes in system reliability between training and testing sessions. Furthermore, it provides evidence that each operator has his/her preferred automation level. Since this preference varies strongly between operators, adaptable automation seems to be suitable to accommodate these large differences.

  14. Design of an Acoustic Target Intrusion Detection System Based on Small-Aperture Microphone Array

    Science.gov (United States)

    Zu, Xingshui; Guo, Feng; Huang, Jingchang; Zhao, Qin; Liu, Huawei; Li, Baoqing; Yuan, Xiaobing

    2017-01-01

    Automated surveillance of remote locations in a wireless sensor network is dominated by the detection algorithm because actual intrusions in such locations are a rare event. Therefore, a detection method with low power consumption is crucial for persistent surveillance to ensure longevity of the sensor networks. A simple and effective two-stage algorithm composed of energy detector (ED) and delay detector (DD) with all its operations in time-domain using small-aperture microphone array (SAMA) is proposed. The algorithm analyzes the quite different velocities between wind noise and sound waves to improve the detection capability of ED in the surveillance area. Experiments in four different fields with three types of vehicles show that the algorithm is robust to wind noise and the probability of detection and false alarm are 96.67% and 2.857%, respectively. PMID:28273838

  15. Design of an Acoustic Target Intrusion Detection System Based on Small-Aperture Microphone Array.

    Science.gov (United States)

    Zu, Xingshui; Guo, Feng; Huang, Jingchang; Zhao, Qin; Liu, Huawei; Li, Baoqing; Yuan, Xiaobing

    2017-03-04

    Automated surveillance of remote locations in a wireless sensor network is dominated by the detection algorithm because actual intrusions in such locations are a rare event. Therefore, a detection method with low power consumption is crucial for persistent surveillance to ensure longevity of the sensor networks. A simple and effective two-stage algorithm composed of energy detector (ED) and delay detector (DD) with all its operations in time-domain using small-aperture microphone array (SAMA) is proposed. The algorithm analyzes the quite different velocities between wind noise and sound waves to improve the detection capability of ED in the surveillance area. Experiments in four different fields with three types of vehicles show that the algorithm is robust to wind noise and the probability of detection and false alarm are 96.67% and 2.857%, respectively.

  16. Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

    Science.gov (United States)

    2016-04-05

    leader and all leaders in the system share a leader secret key ( KRL ) for efficiency purposes. In summary, there are three keys for hierarchical group...keymanagement: leader key ( KRL ), regional key (KR), and group key (KG). These keys are rekeyedproperly, in part or in whole, as events happen in the...each partitioned group will execute GDH to agree on a new leader key KRL . Groupmerge: Two groupsmaymerge into onewhen connectivity resumes. A

  17. Self-Adaptive Systems for Machine Intelligence

    CERN Document Server

    He, Haibo

    2011-01-01

    This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide application

  18. Perimeter intrusion sensors

    International Nuclear Information System (INIS)

    Eaton, M.J.

    1977-01-01

    To obtain an effective perimeter intrusion detection system requires careful sensor selection, procurement, and installation. The selection process involves a thorough understanding of the unique site features and how these features affect the performance of each type of sensor. It is necessary to develop procurement specifications to establish acceptable sensor performance limits. Careful explanation and inspection of critical installation dimensions is required during on-site construction. The implementation of these activities at a particular site is discussed

  19. Meeting Ecologists Requirements with Adaptive Data Acquisition

    DEFF Research Database (Denmark)

    Chang, Marcus; Bonnet, Philippe

    Ecologists instrument ecosystems with in-situ sensing to collect mea- surements. Sensor networks promise to improve on existing data acqui- sition systems by interconnecting stand-alone measurement systems into virtual instruments. Such ecological sensor networks, however, will only fulll...

  20. Adaptive partial volume classification of MRI data

    International Nuclear Information System (INIS)

    Chiverton, John P; Wells, Kevin

    2008-01-01

    Tomographic biomedical images are commonly affected by an imaging artefact known as the partial volume (PV) effect. The PV effect produces voxels composed of a mixture of tissues in anatomical magnetic resonance imaging (MRI) data resulting in a continuity of these tissue classes. Anatomical MRI data typically consist of a number of contiguous regions of tissues or even contiguous regions of PV voxels. Furthermore discontinuities exist between the boundaries of these contiguous image regions. The work presented here probabilistically models the PV effect using spatial regularization in the form of continuous Markov random fields (MRFs) to classify anatomical MRI brain data, simulated and real. A unique approach is used to adaptively control the amount of spatial regularization imposed by the MRF. Spatially derived image gradient magnitude is used to identify the discontinuities between image regions of contiguous tissue voxels and PV voxels, imposing variable amounts of regularization determined by simulation. Markov chain Monte Carlo (MCMC) is used to simulate the posterior distribution of the probabilistic image model. Promising quantitative results are presented for PV classification of simulated and real MRI data of the human brain.

  1. Data Systems vs. Information Systems

    OpenAIRE

    Amatayakul, Margret K.

    1982-01-01

    This paper examines the current status of “hospital information systems” with respect to the distinction between data systems and information systems. It is proposed that the systems currently existing are incomplete data dystems resulting in ineffective information systems.

  2. Ground Motion Prediction Model Using Adaptive Neuro-Fuzzy Inference Systems: An Example Based on the NGA-West 2 Data

    Science.gov (United States)

    Ameur, Mourad; Derras, Boumédiène; Zendagui, Djawed

    2017-12-01

    Adaptive neuro-fuzzy inference systems (ANFIS) are used here to obtain the robust ground motion prediction model (GMPM). Avoiding a priori functional form, ANFIS provides fully data-driven predictive models. A large subset of the NGA-West2 database is used, including 2335 records from 580 sites and 137 earthquakes. Only shallow earthquakes and recordings corresponding to stations with measured V s30 properties are selected. Three basics input parameters are chosen: the moment magnitude (Mw), the Joyner-Boore distance (R JB) and V s30. ANFIS model output is the peak ground acceleration (PGA), peak ground velocity (PGV) and 5% damped pseudo-spectral acceleration (PSA) at periods from 0.01 to 4 s. A procedure similar to the random-effects approach is developed to provide between- and within-event standard deviations. The total standard deviation (SD) varies between [0.303 and 0.360] (log10 units) depending on the period. The ground motion predictions resulting from such simple three explanatory variables ANFIS models are shown to be comparable to the most recent NGA results (e.g., Boore et al., in Earthquake Spectra 30:1057-1085, 2014; Derras et al., in Earthquake Spectra 32:2027-2056, 2016). The main advantage of ANFIS compared to artificial neuronal network (ANN) is its simple and one-off topology: five layers. Our results exhibit a number of physically sound features: magnitude scaling of the distance dependency, near-fault saturation distance increasing with magnitude and amplification on soft soils. The ability to implement ANFIS model using an analytic equation and Excel is demonstrated.

  3. Ground Motion Prediction Model Using Adaptive Neuro-Fuzzy Inference Systems: An Example Based on the NGA-West 2 Data

    Science.gov (United States)

    Ameur, Mourad; Derras, Boumédiène; Zendagui, Djawed

    2018-03-01

    Adaptive neuro-fuzzy inference systems (ANFIS) are used here to obtain the robust ground motion prediction model (GMPM). Avoiding a priori functional form, ANFIS provides fully data-driven predictive models. A large subset of the NGA-West2 database is used, including 2335 records from 580 sites and 137 earthquakes. Only shallow earthquakes and recordings corresponding to stations with measured V s30 properties are selected. Three basics input parameters are chosen: the moment magnitude ( Mw), the Joyner-Boore distance ( R JB) and V s30. ANFIS model output is the peak ground acceleration (PGA), peak ground velocity (PGV) and 5% damped pseudo-spectral acceleration (PSA) at periods from 0.01 to 4 s. A procedure similar to the random-effects approach is developed to provide between- and within-event standard deviations. The total standard deviation (SD) varies between [0.303 and 0.360] (log10 units) depending on the period. The ground motion predictions resulting from such simple three explanatory variables ANFIS models are shown to be comparable to the most recent NGA results (e.g., Boore et al., in Earthquake Spectra 30:1057-1085, 2014; Derras et al., in Earthquake Spectra 32:2027-2056, 2016). The main advantage of ANFIS compared to artificial neuronal network (ANN) is its simple and one-off topology: five layers. Our results exhibit a number of physically sound features: magnitude scaling of the distance dependency, near-fault saturation distance increasing with magnitude and amplification on soft soils. The ability to implement ANFIS model using an analytic equation and Excel is demonstrated.

  4. Electric vehicle data acquisition system

    DEFF Research Database (Denmark)

    Svendsen, Mathias; Winther-Jensen, Mads; Pedersen, Anders Bro

    2014-01-01

    A data acquisition system for electric vehicles is presented. The system connects to the On-board Diagnostic port of newer vehicles, and utilizes the in-vehicle sensor network, as well as auxiliary sensors, to gather data. Data is transmitted continuously to a central database for academic......, by using the On-board Diagnostic port to identify car model and adapt its software accordingly. By utilizing on-board Global Navigation Satellite System, General Packet Radio Service, accelerometer, gyroscope and magnetometer, the system not only provides valuable data for research in the field of electric...

  5. Adaptation in CRISPR-Cas Systems.

    Science.gov (United States)

    Sternberg, Samuel H; Richter, Hagen; Charpentier, Emmanuelle; Qimron, Udi

    2016-03-17

    Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins constitute an adaptive immune system in prokaryotes. The system preserves memories of prior infections by integrating short segments of foreign DNA, termed spacers, into the CRISPR array in a process termed adaptation. During the past 3 years, significant progress has been made on the genetic requirements and molecular mechanisms of adaptation. Here we review these recent advances, with a focus on the experimental approaches that have been developed, the insights they generated, and a proposed mechanism for self- versus non-self-discrimination during the process of spacer selection. We further describe the regulation of adaptation and the protein players involved in this fascinating process that allows bacteria and archaea to harbor adaptive immunity. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks

    Directory of Open Access Journals (Sweden)

    Tao Ma

    2016-10-01

    Full Text Available The development of intrusion detection systems (IDS that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC and deep neural network (DNN algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN, support vector machine (SVM, random forest (RF and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks.

  7. DataFed: A Federated Data System for Visualization and Analysis of Spatio-Temporal Air Quality Data

    Science.gov (United States)

    Husar, R. B.; Hoijarvi, K.

    2017-12-01

    DataFed is a distributed web-services-based computing environment for accessing, processing, and visualizing atmospheric data in support of air quality science and management. The flexible, adaptive environment facilitates the access and flow of atmospheric data from provider to users by enabling the creation of user-driven data processing/visualization applications. DataFed `wrapper' components, non-intrusively wrap heterogeneous, distributed datasets for access by standards-based GIS web services. The mediator components (also web services) map the heterogeneous data into a spatio-temporal data model. Chained web services provide homogeneous data views (e.g., geospatial, time views) using a global multi-dimensional data model. In addition to data access and rendering, the data processing component services can be programmed for filtering, aggregation, and fusion of multidimensional data. A complete application software is written in a custom made data flow language. Currently, the federated data pool consists of over 50 datasets originating from globally distributed data providers delivering surface-based air quality measurements, satellite observations, emissions data as well as regional and global-scale air quality models. The web browser-based user interface allows point and click navigation and browsing the XYZT multi-dimensional data space. The key applications of DataFed are for exploring spatial pattern of pollutants, seasonal, weekly, diurnal cycles and frequency distributions for exploratory air quality research. Since 2008, DataFed has been used to support EPA in the implementation of the Exceptional Event Rule. The data system is also used at universities in the US, Europe and Asia.

  8. Saltwater intrusion in the Floridan aquifer system near downtown Brunswick, Georgia, 1957–2015

    Science.gov (United States)

    Cherry, Gregory S.; Peck, Michael

    2017-02-16

    IntroductionThe Floridan aquifer system (FAS) consists of the Upper Floridan aquifer (UFA), an intervening confining unit of highly variable properties, and the Lower Floridan aquifer (LFA). The UFA and LFA are primarily composed of Paleocene- to Oligocene-age carbonate rocks that include, locally, Upper Cretaceous rocks. The FAS extends from coastal areas in southeastern South Carolina and continues southward and westward across the coastal plain of Georgia and Alabama, and underlies all of Florida. The thickness of the FAS varies from less than 100 feet (ft) in aquifer outcrop areas of South Carolina to about 1,700 ft near the city of Brunswick, Georgia.Locally, in southeastern Georgia and the Brunswick– Glynn County area, the UFA consists of an upper water-bearing zone (UWBZ) and a lower water-bearing zone (LWBZ), as identified by Wait and Gregg (1973), with aquifer test data indicating the upper zone has higher productivity than the lower zone. Near the city of Brunswick, the LFA is composed of two permeable zones: an early middle Eocene-age upper permeable zone (UPZ) and a highly permeable lower zone of limestone (LPZ) of Paleocene and Late Cretaceous age that includes a deeply buried, cavernous, saline water-bearing unit known as the Fernandina permeable zone. Maslia and Prowell (1990) inferred the presence of major northeast–southwest trending faults through the downtown Brunswick area based on structural analysis of geophysical data, northeastward elongation of the potentiometric surface of the UFA, and breaches in the local confining unit that influence the area of chloride contamination. Pronounced horizontal and vertical hydraulic head gradients, caused by pumping in the UFA, allow saline water from the FPZ to migrate upward into the UFA through this system of faults and conduits.Saltwater was first detected in the FAS in wells completed in the UFA near the southern part of the city of Brunswick in late 1957. By the 1970s, a plume of groundwater

  9. Adaptive Dialogue Systems for Assistive Living Environments

    Science.gov (United States)

    Papangelis, Alexandros

    2013-01-01

    Adaptive Dialogue Systems (ADS) are intelligent systems, able to interact with users via multiple modalities, such as speech, gestures, facial expressions and others. Such systems are able to make conversation with their users, usually on a specific, narrow topic. Assistive Living Environments are environments where the users are by definition not…

  10. Meeting Ecologists Requirements with Adaptive Data Acquisition

    DEFF Research Database (Denmark)

    Chang, Marcus; Bonnet, Philippe

    Ecologists instrument ecosystems with in-situ sensing to collect mea- surements. Sensor networks promise to improve on existing data acqui- sition systems by interconnecting stand-alone measurement systems into virtual instruments. Such ecological sensor networks, however, will only fulll...... their potential if they meet the scientists requirements. In an ideal world, an ecologist expresses requirements in terms of a target dataset, which the sensor network then actually collects and stores. In fact, failures occur and interesting events happen making uniform, systematic ecosys- tem sampling neither...

  11. Self-adaptive iris image acquisition system

    Science.gov (United States)

    Dong, Wenbo; Sun, Zhenan; Tan, Tieniu; Qiu, Xianchao

    2008-03-01

    Iris image acquisition is the fundamental step of the iris recognition, but capturing high-resolution iris images in real-time is very difficult. The most common systems have small capture volume and demand users to fully cooperate with machines, which has become the bottleneck of iris recognition's application. In this paper, we aim at building an active iris image acquiring system which is self-adaptive to users. Two low resolution cameras are co-located in a pan-tilt-unit (PTU), for face and iris image acquisition respectively. Once the face camera detects face region in real-time video, the system controls the PTU to move towards the eye region and automatically zooms, until the iris camera captures an clear iris image for recognition. Compared with other similar works, our contribution is that we use low-resolution cameras, which can transmit image data much faster and are much cheaper than the high-resolution cameras. In the system, we use Haar-like cascaded feature to detect faces and eyes, linear transformation to predict the iris camera's position, and simple heuristic PTU control method to track eyes. A prototype device has been established, and experiments show that our system can automatically capture high-quality iris image in the range of 0.6m×0.4m×0.4m in average 3 to 5 seconds.

  12. Complex and Adaptive Dynamical Systems A Primer

    CERN Document Server

    Gros, Claudius

    2011-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  13. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2007-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  14. Wireless Sensor Network Based Smart Grid Communications: Cyber Attacks, Intrusion Detection System and Topology Control

    Directory of Open Access Journals (Sweden)

    Lipi Chhaya

    2017-01-01

    Full Text Available The existing power grid is going through a massive transformation. Smart grid technology is a radical approach for improvisation in prevailing power grid. Integration of electrical and communication infrastructure is inevitable for the deployment of Smart grid network. Smart grid technology is characterized by full duplex communication, automatic metering infrastructure, renewable energy integration, distribution automation and complete monitoring and control of entire power grid. Wireless sensor networks (WSNs are small micro electrical mechanical systems that are deployed to collect and communicate the data from surroundings. WSNs can be used for monitoring and control of smart grid assets. Security of wireless sensor based communication network is a major concern for researchers and developers. The limited processing capabilities of wireless sensor networks make them more vulnerable to cyber-attacks. The countermeasures against cyber-attacks must be less complex with an ability to offer confidentiality, data readiness and integrity. The address oriented design and development approach for usual communication network requires a paradigm shift to design data oriented WSN architecture. WSN security is an inevitable part of smart grid cyber security. This paper is expected to serve as a comprehensive assessment and analysis of communication standards, cyber security issues and solutions for WSN based smart grid infrastructure.

  15. Adaptive processes in economic systems

    CERN Document Server

    Murphy, Roy E

    1965-01-01

    In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;. methods for low-rank m

  16. Programmable Ultra-Lightweight System Adaptable Radio

    Science.gov (United States)

    Werkheiser, Arthur

    2015-01-01

    The programmable ultra-lightweight system adaptable radio (PULSAR) is a NASA Marshall Space Flight Center transceiver designed for the CubeSat market, but has the potential for other markets. The PULSAR project aims to reduce size, weight, and power while increasing telemetry data rate. The current version of the PULSAR has a mass of 2.2 kg and a footprint of 10.8 cm2. The height depends on the specific configuration. The PULSAR S-Band Communications Subsystem is an S- and X-band transponder system comprised of a receiver/detector (receiver) element, a transmitter element(s), and related power distribution, command, control, and telemetry element for operation and information interfaces. It is capable of receiving commands, encoding and transmitting telemetry, as well as providing tracking data in a manner compatible with Earthbased ground stations, near Earth network, and deep space network station resources. The software-defined radio's (SDR's) data format characteristics can be defined and reconfigured during spaceflight or prior to launch. The PULSAR team continues to evolve the SDR to improve the performance and form factor to meet the requirements that the CubeSat market space requires. One of the unique features is that the actual radio design can change (somewhat), but not require any hardware modifications due to the use of field programmable gate arrays.

  17. Adaptive Filtering and System Identification

    National Research Council Canada - National Science Library

    Gibson, Steve

    2007-01-01

    .... Additional application areas include optical wireless communication systems, blind identification and deconvolution in wireless communications, and active control of noise and vibration. This report discusses recent collaborations with the Air Force Research Laboratory (AFRL) and industry.

  18. Orthodontic intrusion : Conventional and mini-implant assisted intrusion mechanics

    Directory of Open Access Journals (Sweden)

    Anup Belludi

    2012-01-01

    intrusion has revolutionized orthodontic anchorage and biomechanics by making anchorage perfectly stable. This article addresses various conventional clinical intrusion mechanics and especially intrusion using mini-implants that have proven effective over the years for intrusion of maxillary anteriors.

  19. Petroleum Vapor Intrusion

    Science.gov (United States)

    One type of vapor intrusion is PVI, in which vapors from petroleum hydrocarbons such as gasoline, diesel, or jet fuel enter a building. Intrusion of contaminant vapors into indoor spaces is of concern.

  20. CONSTRUCTIVE MODEL OF ADAPTATION OF DATA STRUCTURES IN RAM. PART II. CONSTRUCTORS OF SCENARIOS AND ADAPTATION PROCESSES

    Directory of Open Access Journals (Sweden)

    V. I. Shynkarenko

    2016-04-01

    Full Text Available Purpose.The second part of the paper completes presentation of constructive and the productive structures (CPS, modeling adaptation of data structures in memory (RAM. The purpose of the second part in the research is to develop a model of process of adaptation data in a RAM functioning in different hardware and software environments and scenarios of data processing. Methodology. The methodology of mathematical and algorithmic constructionism was applied. In this part of the paper, changes were developed the constructors of scenarios and adaptation processes based on a generalized CPS through its transformational conversions. Constructors are interpreted, specialized CPS. Were highlighted the terminal alphabets of the constructor scenarios in the form of data processing algorithms and the constructor of adaptation – in the form of algorithmic components of the adaptation process. The methodology involves the development of substitution rules that determine the output process of the relevant structures. Findings. In the second part of the paper, system is represented by CPS modeling adaptation data placement in the RAM, namely, constructors of scenarios and of adaptation processes. The result of the implementation of constructor of scenarios is a set of data processing operations in the form of text in the language of programming C#, constructor of the adaptation processes – a process of adaptation, and the result the process of adaptation – the adapted binary code of processing data structures. Originality. For the first time proposed the constructive model of data processing – the scenario that takes into account the order and number of calls to the various elements of data structures and adaptation of data structures to the different hardware and software environments. At the same the placement of data in RAM and processing algorithms are adapted. Constructionism application in modeling allows to link data models and algorithms for

  1. Adaptive data management in the ARC Grid middleware

    Science.gov (United States)

    Cameron, D.; Gholami, A.; Karpenko, D.; Konstantinov, A.

    2011-12-01

    The Advanced Resource Connector (ARC) Grid middleware was designed almost 10 years ago, and has proven to be an attractive distributed computing solution and successful in adapting to new data management and storage technologies. However, with an ever-increasing user base and scale of resources to manage, along with the introduction of more advanced data transfer protocols, some limitations in the current architecture have become apparent. The simple first-in first-out approach to data transfer leads to bottlenecks in the system, as does the built-in assumption that all data is immediately available from remote data storage. We present an entirely new data management architecture for ARC which aims to alleviate these problems, by introducing a three-layer structure. The top layer accepts incoming requests for data transfer and directs them to the middle layer, which schedules individual transfers and negotiates with various intermediate catalog and storage systems until the physical file is ready to be transferred. The lower layer performs all operations which use large amounts of bandwidth, i.e. the physical data transfer. Using such a layered structure allows more efficient use of the available bandwidth as well as enabling late-binding of jobs to data transfer slots based on a priority system. Here we describe in full detail the design and implementation of the new system.

  2. Some Features of Pressure Evolution in Systems “Non-Wetting Liquid - Nanoporous Medium” at Impact Intrusion

    Science.gov (United States)

    Byrkin, V. A.; Belogorlov, A. A.; Paryohin, D. A.; Mitrofanova, A. S.

    2017-04-01

    The last few decades systems consisting of nanoporous medium dispersed in a non-wetting liquid cause an increased interest from both the practical and theoretical points of view. Non-wetting liquid can infiltrate into the porous medium only with an excess pressure. Liquid infiltration tends to increase the solid-liquid interfacial energy and the absorbed energy is proportional to the specific surface area of the medium. Therefore this energy for nanoporous media can reach several orders of magnitude superior to traditional damping materials and shape-memory materials. As a consequence, the prospects of using devices based on systems consisting of a nanoporous medium immersed in a non-wetting liquid associated mainly with the absorption of mechanical energy of impact or explosion. The paper presents the results of experimental studies of impact intrusion the systems of industrially produced hydrophobic silicas Fluka 100 C8 and Fluka 100 C18 with distilled water. With increasing the impact energies nontrivial pattern of pressure changes in the system over time is observed.

  3. Preliminary images from an adaptive imaging system

    NARCIS (Netherlands)

    Griffiths, J.A.; Metaxas, M.G.; Pani, S.; Schulerud, H.; Esbrand, C.; Royle, G.J.; Price, B.; Rokvic, T.; Longo, R.; Asimidis, A.; Bletsas, E.; Cavouras, D.; Fant, A.; Gasiorek, P.; Georgiou, H.; Hall, G.; Jones, J.; Leaver, J.; Li, G.; Machin, D.; Manthos, N.; Matheson, J.; Noy, M.; Østby, J.M.; Psomadellis, F.; van der Stelt, P.F.; Theodoridis, S.; Triantis, F.; Turchetta, R.; Venanzi, C.; Speller, R.D.

    2008-01-01

    I-ImaS (Intelligent Imaging Sensors) is a European project aiming to produce real-time adaptive X-ray imaging systems using Monolithic Active Pixel Sensors (MAPS) to create images with maximum diagnostic information within given dose constraints. Initial systems concentrate on mammography and

  4. Simple adaptive control system design trades

    NARCIS (Netherlands)

    Mooij, E.

    2017-01-01

    In the design of a Model Reference Adaptive Control system, a reference model serves as the (well-known) basis through which system and user requirements can find their way into the design. By tuning the design parameters, the response of the actual vehicle should track the response of the

  5. Intrusion scenarios in fusion waste disposal sites

    International Nuclear Information System (INIS)

    Zucchetti, M.; Zucchetti, M.; Rocco, P.

    1998-01-01

    Results of analyses on human intrusions into repositories of fusion radioactive waste are presented. The main topics are: duration of the institutional control, occurrence of intrusion, intrusion scenarios, acceptable risk limits and probabilistic data. Application to fusion waste repositories is implemented with a computational model: wells drilling is considered as the possible scenario. Doses and risks to intruder for different SEAFP-2 cases turn out to be very small. No intervention to reduce the hazard is necessary. (authors)

  6. Intrusion scenarios in fusion waste disposal sites

    Energy Technology Data Exchange (ETDEWEB)

    Zucchetti, M. [European Commission, JRC, Institute for Advanced Material, Ispra, Vatican City State, Holy See (Italy); Zucchetti, M.; Rocco, P. [Energetics Dept., Polytechnic of Turin (Italy)

    1998-07-01

    Results of analyses on human intrusions into repositories of fusion radioactive waste are presented. The main topics are: duration of the institutional control, occurrence of intrusion, intrusion scenarios, acceptable risk limits and probabilistic data. Application to fusion waste repositories is implemented with a computational model: wells drilling is considered as the possible scenario. Doses and risks to intruder for different SEAFP-2 cases turn out to be very small. No intervention to reduce the hazard is necessary. (authors)

  7. Foundations for Survivable System Development: Service Traces, Intrusion Traces, and Evaluation Models

    National Research Council Canada - National Science Library

    Linger, Richard

    2001-01-01

    .... On the system side, survivability specifications can be defined by essential-service traces that map essential-service workflows, derived from user requirements, into system component dependencies...

  8. Coupled human-water system dynamics of saltwater intrusion in the low coastal plain of the Po River, Ravenna, Italy

    Science.gov (United States)

    Lauriola, Ilaria; Ciriello, Valentina; Antonellini, Marco; Pande, Saket

    2017-04-01

    Human activities affect the whole hydrological cycle with possible severe consequences on ecosystem services. Human-water interaction follows complex dynamics that can't be addressed only through the analysis of water withdrawals and contamination processes. As such, comprehensive analysis strategies based on a socio-hydrology approach may allow to deeply understand the co-evolution of human and water systems. Here, we focus on the low coastal plain of the Po river in the south of Ravenna (Italy), which is adjacent to the North Adriatic sea. In particular, our study regards a basin characterized by a land reclamation drainage system, given the low topography which reaches in some places 1 m below sea level. In this area, the thin phreatic coastal aquifer is affected by a relevant salinization process and characterized by the presence of valuable water-dependent ecosystems such as pine forests and wetlands. Groundwater salinization is mainly caused by seawater intrusion due to the hydraulic gradient landwards that is enhanced by land subsidence, land use and drainage allowing for agriculture and settlements. Such a complex scenario involves environmental, social and economic interests. We study the intricate system of relationships occurring between a set of socio-hydrological state variables of interest based on the dynamic analysis of land use changes in the study area that mainly affect groundwater recharge and the availability of freshwater for ecosystem and agriculture activities.

  9. Adaptation in the auditory system: an overview

    Directory of Open Access Journals (Sweden)

    David ePérez-González

    2014-02-01

    Full Text Available The early stages of the auditory system need to preserve the timing information of sounds in order to extract the basic features of acoustic stimuli. At the same time, different processes of neuronal adaptation occur at several levels to further process the auditory information. For instance, auditory nerve fiber responses already experience adaptation of their firing rates, a type of response that can be found in many other auditory nuclei and may be useful for emphasizing the onset of the stimuli. However, it is at higher levels in the auditory hierarchy where more sophisticated types of neuronal processing take place. For example, stimulus-specific adaptation, where neurons show adaptation to frequent, repetitive stimuli, but maintain their responsiveness to stimuli with different physical characteristics, thus representing a distinct kind of processing that may play a role in change and deviance detection. In the auditory cortex, adaptation takes more elaborate forms, and contributes to the processing of complex sequences, auditory scene analysis and attention. Here we review the multiple types of adaptation that occur in the auditory system, which are part of the pool of resources that the neurons employ to process the auditory scene, and are critical to a proper understanding of the neuronal mechanisms that govern auditory perception.

  10. Managing adaptively for multifunctionality in agricultural systems.

    Science.gov (United States)

    Hodbod, Jennifer; Barreteau, Olivier; Allen, Craig; Magda, Danièle

    2016-12-01

    The critical importance of agricultural systems for food security and as a dominant global landcover requires management that considers the full dimensions of system functions at appropriate scales, i.e. multifunctionality. We propose that adaptive management is the most suitable management approach for such goals, given its ability to reduce uncertainty over time and support multiple objectives within a system, for multiple actors. As such, adaptive management may be the most appropriate method for sustainably intensifying production whilst increasing the quantity and quality of ecosystem services. However, the current assessment of performance of agricultural systems doesn't reward ecosystem service provision. Therefore, we present an overview of the ecosystem functions agricultural systems should and could provide, coupled with a revised definition for assessing the performance of agricultural systems from a multifunctional perspective that, when all satisfied, would create adaptive agricultural systems that can increase production whilst ensuring food security and the quantity and quality of ecosystem services. The outcome of this high level of performance is the capacity to respond to multiple shocks without collapse, equity and triple bottom line sustainability. Through the assessment of case studies, we find that alternatives to industrialized agricultural systems incorporate more functional goals, but that there are mixed findings as to whether these goals translate into positive measurable outcomes. We suggest that an adaptive management perspective would support the implementation of a systematic analysis of the social, ecological and economic trade-offs occurring within such systems, particularly between ecosystem services and functions, in order to provide suitable and comparable assessments. We also identify indicators to monitor performance at multiple scales in agricultural systems which can be used within an adaptive management framework to increase

  11. Managing adaptively for multifunctionality in agricultural systems

    Science.gov (United States)

    Hodbod, Jennifer; Barreteau, Olivier; Allen, Craig R.; Magda, Danièle

    2016-01-01

    The critical importance of agricultural systems for food security and as a dominant global landcover requires management that considers the full dimensions of system functions at appropriate scales, i.e. multifunctionality. We propose that adaptive management is the most suitable management approach for such goals, given its ability to reduce uncertainty over time and support multiple objectives within a system, for multiple actors. As such, adaptive management may be the most appropriate method for sustainably intensifying production whilst increasing the quantity and quality of ecosystem services. However, the current assessment of performance of agricultural systems doesn’t reward ecosystem service provision. Therefore, we present an overview of the ecosystem functions agricultural systems should and could provide, coupled with a revised definition for assessing the performance of agricultural systems from a multifunctional perspective that, when all satisfied, would create adaptive agricultural systems that can increase production whilst ensuring food security and the quantity and quality of ecosystem services. The outcome of this high level of performance is the capacity to respond to multiple shocks without collapse, equity and triple bottom line sustainability. Through the assessment of case studies, we find that alternatives to industrialized agricultural systems incorporate more functional goals, but that there are mixed findings as to whether these goals translate into positive measurable outcomes. We suggest that an adaptive management perspective would support the implementation of a systematic analysis of the social, ecological and economic trade-offs occurring within such systems, particularly between ecosystem services and functions, in order to provide suitable and comparable assessments. We also identify indicators to monitor performance at multiple scales in agricultural systems which can be used within an adaptive management framework to

  12. Unsupervised algorithms for intrusion detection and identification in wireless ad hoc sensor networks

    Science.gov (United States)

    Hortos, William S.

    2009-05-01

    In previous work by the author, parameters across network protocol layers were selected as features in supervised algorithms that detect and identify certain intrusion attacks on wireless ad hoc sensor networks (WSNs) carrying multisensor data. The algorithms improved the residual performance of the intrusion prevention measures provided by any dynamic key-management schemes and trust models implemented among network nodes. The approach of this paper does not train algorithms on the signature of known attack traffic, but, instead, the approach is based on unsupervised anomaly detection techniques that learn the signature of normal network traffic. Unsupervised learning does not require the data to be labeled or to be purely of one type, i.e., normal or attack traffic. The approach can be augmented to add any security attributes and quantified trust levels, established during data exchanges among nodes, to the set of cross-layer features from the WSN protocols. A two-stage framework is introduced for the security algorithms to overcome the problems of input size and resource constraints. The first stage is an unsupervised clustering algorithm which reduces the payload of network data packets to a tractable size. The second stage is a traditional anomaly detection algorithm based on a variation of support vector machines (SVMs), whose efficiency is improved by the availability of data in the packet payload. In the first stage, selected algorithms are adapted to WSN platforms to meet system requirements for simple parallel distributed computation, distributed storage and data robustness. A set of mobile software agents, acting like an ant colony in securing the WSN, are distributed at the nodes to implement the algorithms. The agents move among the layers involved in the network response to the intrusions at each active node and trustworthy neighborhood, collecting parametric values and executing assigned decision tasks. This minimizes the need to move large amounts

  13. Evolving Systems and Adaptive Key Component Control

    Science.gov (United States)

    Frost, Susan A.; Balas, Mark J.

    2009-01-01

    We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.

  14. Alerts Visualization and Clustering in Network-based Intrusion Detection

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Dr. Li [University of Tennessee; Gasior, Wade C [ORNL; Dasireddy, Swetha [University of Tennessee

    2010-04-01

    Today's Intrusion detection systems when deployed on a busy network overload the network with huge number of alerts. This behavior of producing too much raw information makes it less effective. We propose a system which takes both raw data and Snort alerts to visualize and analyze possible intrusions in a network. Then we present with two models for the visualization of clustered alerts. Our first model gives the network administrator with the logical topology of the network and detailed information of each node that involves its associated alerts and connections. In the second model, flocking model, presents the network administrator with the visual representation of IDS data in which each alert is represented in different color and the alerts with maximum similarity move together. This gives network administrator with the idea of detecting various of intrusions through visualizing the alert patterns.

  15. Computational identification of adaptive mutants using the VERT system

    Directory of Open Access Journals (Sweden)

    Winkler James

    2012-04-01

    Full Text Available Background Evolutionary dynamics of microbial organisms can now be visualized using the Visualizing Evolution in Real Time (VERT system, in which several isogenic strains expressing different fluorescent proteins compete during adaptive evolution and are tracked using fluorescent cell sorting to construct a population history over time. Mutations conferring enhanced growth rates can be detected by observing changes in the fluorescent population proportions. Results Using data obtained from several VERT experiments, we construct a hidden Markov-derived model to detect these adaptive events in VERT experiments without external intervention beyond initial training. Analysis of annotated data revealed that the model achieves consensus with human annotation for 85-93% of the data points when detecting adaptive events. A method to determine the optimal time point to isolate adaptive mutants is also introduced. Conclusions The developed model offers a new way to monitor adaptive evolution experiments without the need for external intervention, thereby simplifying adaptive evolution efforts relying on population tracking. Future efforts to construct a fully automated system to isolate adaptive mutants may find the algorithm a useful tool.

  16. Adaptive control of solar energy collector systems

    CERN Document Server

    Lemos, João M; Igreja, José M

    2014-01-01

    This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts

  17. Real Time Adaptive Stream-oriented Geo-data Filtering

    Directory of Open Access Journals (Sweden)

    A. A. Golovkov

    2016-01-01

    Full Text Available The cutting-edge engineering maintenance software systems of various objects are aimed at processing of geo-location data coming from the employees’ mobile devices in real time. To reduce the amount of transmitted data such systems, usually, use various filtration methods of geo-coordinates recorded directly on mobile devices.The paper identifies the reasons for errors of geo-data coming from different sources, and proposes an adaptive dynamic method to filter geo-location data. Compared with the static method previously described in the literature [1] the approach offers to align adaptively the filtering threshold with changing characteristics of coordinates from many sources of geo-location data.To evaluate the efficiency of the developed filter method have been involved about 400 thousand points, representing motion paths of different type (on foot, by car and high-speed train and parking (indoors, outdoors, near high-rise buildings to take data from different mobile devices. Analysis of results has shown that the benefits of the proposed method are the more precise location of long parking (up to 6 hours and coordinates when user is in motion, the capability to provide steam-oriented filtering of data from different sources that allows to use the approach in geo-information systems, providing continuous monitoring of the location in streamoriented data processing in real time. The disadvantage is a little bit more computational complexity and increasing amount of points of the final track as compared to other filtration techniques.In general, the developed approach enables a significant quality improvement of displayed paths of moving mobile objects.

  18. Environmentally-adapted local energy systems

    Energy Technology Data Exchange (ETDEWEB)

    Moe, N.; Oefverholm, E. [NUTEK, Stockholm (Sweden); Andersson, Owe [EKAN Gruppen (Sweden); Froste, H. [Swedish Environmental Protection Agency, Stockholm (Sweden)

    1997-10-01

    Energy companies, municipalities, property companies, firms of consultants, environmental groups and individuals are examples of players working locally to shape environmentally adapted energy systems. These players have needed information making them better able to make decisions on cost-efficient, environmentally-adapted energy systems. This book answers many of the questions they have put. The volume is mainly based on Swedish handbooks produced by the Swedish National Board for Industrial and Technical Development, NUTEK, together with the Swedish Environmental Protection Agency. These handbooks have been used in conjunction with municipal energy planning, local Agenda 21 work, to provide a basis for deciding on concrete local energy systems. The contents in brief: -The book throws new light on the concept of energy efficiency; -A section on the environment compares how air-polluting emissions vary with different methods of energy production; -A section contains more than 40 ideas for measures which can be profitable, reduce energy consumption and the impact on the environment all at the same time; -The book gives concrete examples of new, alternative and environmentally-adapted local energy systems. More efficient use of energy is included as a possible change of energy system; -The greatest emphasis is laid upon alternative energy systems for heating. It may be heating in a house, block of flats, office building or school; -Finally, there are examples of environmentally-adapted local energy planning.

  19. Modeling Adaptive Behavior for Systems Design

    DEFF Research Database (Denmark)

    Rasmussen, Jens

    1994-01-01

    Field studies in modern work systems and analysis of recent major accidents have pointed to a need for better models of the adaptive behavior of individuals and organizations operating in a dynamic and highly competitive environment. The paper presents a discussion of some key characteristics...... of the predictive models required for the design of work supports systems, that is,information systems serving as the human-work interface. Three basic issues are in focus: 1.) Some fundamental problems in analysis and modeling modern dynamic work systems caused by the adaptive nature of human behavior; 2.......) The basic difference between the models of system functions used in engineering and design and those evolving from basic research within the various academic disciplines and finally 3.) The models and methods required for closed-loop, feedback system design....

  20. Method and apparatus for distributed intrusion protection system for ultra high bandwidth networks

    Science.gov (United States)

    Goranson, Craig A.; Burnette, John R.; Greitzer, Frank L.; McMillan, Bryan H.

    2013-10-15

    A method for providing security to a network having a data stream with a plurality of portions of data, each having differing levels of sensitivity. The data stream is interrogated to determine the presence of predetermined characteristics associated with at least one of the portions of data within the data stream. At least one of the portions of data is then characterized, based upon the portion of data exhibiting a predetermined combination of characteristics, wherein the predetermined combination of characteristics is related to the sensitivity of the portion of data. The portions of the data stream are then distributed into a plurality of different channels, each of the channels associated with different level of sensitivity.

  1. Data acquisition and test system software

    International Nuclear Information System (INIS)

    Bourgeois, N.A. Jr.

    1979-03-01

    Sandia Laboratories has been assigned the task by the Base and Installation Security Systems (BISS) Program Office to develop various aspects of perimeter security systems. One part of this effort involves the development of advanced signal processing techniques to reduce the false and nuisance alarms from sensor systems while improving the probability of intrusion detection. The need existed for both data acquisition hardware and software. Also, the hardware is used to implement and test the signal processing algorithms in real time. The hardware developed for this signal processing task is the Data Acquisition and Test System (DATS). The programs developed for use on DATS are described. The descriptions are taken directly from the documentation included within the source programs themselves

  2. Workload modelling for data-intensive systems

    CERN Document Server

    Lassnig, Mario

    This thesis presents a comprehensive study built upon the requirements of a global data-intensive system, built for the ATLAS Experiment at CERN's Large Hadron Collider. First, a scalable method is described to capture distributed data management operations in a non-intrusive way. These operations are collected into a globally synchronised sequence of events, the workload. A comparative analysis of this new data-intensive workload against existing computational workloads is conducted, leading to the discovery of the importance of descriptive attributes in the operations. Existing computational workload models only consider the arrival rates of operations, however, in data-intensive systems the correlations between attributes play a central role. Furthermore, the detrimental effect of rapid correlated arrivals, so called bursts, is assessed. A model is proposed that can learn burst behaviour from captured workload, and in turn forecast potential future bursts. To help with the creation of a full representative...

  3. Intrusion Prevention System Based on the Aççess Control Mechanism in the Operating System Miçrosoft Windows

    Directory of Open Access Journals (Sweden)

    V. S. Matveeva

    2012-03-01

    Full Text Available It is suggested to implement an intrusion prevention system based on the access control mechanism of Microsoft Windows operating system to restrict the execution of malicious code. Most of the existing computer security facilities use behavioral and heuristic analyses based on an undocumented method of system calls interception that is not an uniform approach in designing of proactive security mechanism. The IPS is portable among different versions of the OS because it is implemented with documented functions only, it does not need to be updated and uses less system resources in comparison with another protection systems. The system protects from zero-day malware and therefore prevents companies from online-banking fraud that is a very actual problem of information security nowadays.

  4. Potential effects of deepening the St. Johns River navigation channel on saltwater intrusion in the surficial aquifer system, Jacksonville, Florida

    Science.gov (United States)

    Bellino, Jason C.; Spechler, Rick M.

    2013-01-01

    The U.S. Army Corps of Engineers (USACE) has proposed dredging a 13-mile reach of the St. Johns River navigation channel in Jacksonville, Florida, deepening it to depths between 50 and 54 feet below North American Vertical Datum of 1988. The dredging operation will remove about 10 feet of sediments from the surficial aquifer system, including limestone in some locations. The limestone unit, which is in the lowermost part of the surficial aquifer system, supplies water to domestic wells in the Jacksonville area. Because of density-driven hydrodynamics of the St. Johns River, saline water from the Atlantic Ocean travels upstream as a saltwater “wedge” along the bottom of the channel, where the limestone is most likely to be exposed by the proposed dredging. A study was conducted to determine the potential effects of navigation channel deepening in the St. Johns River on salinity in the adjacent surficial aquifer system. Simulations were performed with each of four cross-sectional, variable-density groundwater-flow models, developed using SEAWAT, to simulate hypothetical changes in salinity in the surficial aquifer system as a result of dredging. The cross-sectional models were designed to incorporate a range of hydrogeologic conceptualizations to estimate the effect of uncertainty in hydrogeologic properties. The cross-sectional models developed in this study do not necessarily simulate actual projected conditions; instead, the models were used to examine the potential effects of deepening the navigation channel on saltwater intrusion in the surficial aquifer system under a range of plausible hypothetical conditions. Simulated results for modeled conditions indicate that dredging will have little to no effect on salinity variations in areas upstream of currently proposed dredging activities. Results also indicate little to no effect in any part of the surficial aquifer system along the cross section near River Mile 11 or in the water-table unit along the cross

  5. Final Report - Regulatory Considerations for Adaptive Systems

    Science.gov (United States)

    Wilkinson, Chris; Lynch, Jonathan; Bharadwaj, Raj

    2013-01-01

    This report documents the findings of a preliminary research study into new approaches to the software design assurance of adaptive systems. We suggest a methodology to overcome the software validation and verification difficulties posed by the underlying assumption of non-adaptive software in the requirementsbased- testing verification methods in RTCA/DO-178B and C. An analysis of the relevant RTCA/DO-178B and C objectives is presented showing the reasons for the difficulties that arise in showing satisfaction of the objectives and suggested additional means by which they could be satisfied. We suggest that the software design assurance problem for adaptive systems is principally one of developing correct and complete high level requirements and system level constraints that define the necessary system functional and safety properties to assure the safe use of adaptive systems. We show how analytical techniques such as model based design, mathematical modeling and formal or formal-like methods can be used to both validate the high level functional and safety requirements, establish necessary constraints and provide the verification evidence for the satisfaction of requirements and constraints that supplements conventional testing. Finally the report identifies the follow-on research topics needed to implement this methodology.

  6. Non-Intrusive Appliance Recognition

    NARCIS (Netherlands)

    Hoogsteen, G; Hoogsteen, Gerwin; Krist, J.O.; Bakker, Vincent; Smit, Gerardus Johannes Maria

    2012-01-01

    Energy conservation becomes more important nowadays. The use of smart meters and, in the near future, smart appliances, are the key to achieve reduction in energy consumption. This research proposes a non-intrusive appliance monitor and recognition system for implementation on an embedded system.

  7. A Non-Intrusive Approach to Enhance Legacy Embedded Control Systems with Cyber Protection Features

    Science.gov (United States)

    Ren, Shangping; Chen, Nianen; Yu, Yue; Poirot, Pierre; Kwiat, Kevin; Tsai, Jeffrey J. P.

    Trust is cast as a continuous re-evaluation: a system’s reliability and security are scrutinized, not just prior to, but during its deployment. This approach to maintaining trust is specifically applied to distributed and embedded control systems. Unlike general purpose systems, distributed and embedded control systems, such as power grid control systems and water treatment systems, etc., generally have a 24x7 availability requirement. Hence, upgrading or adding new cyber protection features into these systems in order to sustain them when faults caused by cyber attacks occur, is often difficult to achieve and inhibits the evolution of these systems into a cyber environment. In this chapter, we present a solution for extending the capabilities of existing systems while simultaneously maintaining the stability of the current systems. An externalized survivability management scheme based on the observe-reason-modify paradigm is applied, which decomposes the cyber attack protection process into three orthogonal subtasks: observation, evaluation and protection. This architecture provides greater flexibility and has a resolvability attribute- it can utilize emerging techniques; yet requires either minimal modifications or even no modifications whatsoever to the controlled infrastructures. The approach itself is general and can be applied to a broad class of observable systems.

  8. Geochronology of the Neogene intrusive magmatism of the Oaș—Gutâi Mountains, Eastern Carpathians (NW Romania)

    Science.gov (United States)

    Kovacs, Marinel; Pécskay, Zoltán; Fülöp, Alexandrina; Jurje, Maria; Edelstein, Oscar

    2013-12-01

    Earlier geological work in the Oaș-Gutâi Mts (OG), Eastern Carpathians, has revealed the extensive presence of shallow subvolcanic intrusive bodies, both exposed on the surface and covered by Paleogene-Neogene sedimentary sequences and Neogene volcanic formations. This study is based on detailed mapping and sampling of the OG Neogene intrusive magmatic rocks. Thirty seven representative intrusions (sills, dykes, microlaccoliths, etc.) were selected for radiometric dating. These intrusions show a wide variety of petrographic rock-types: from microgabbros to microgranodiorites and from basalts to andesites. However, the intrusions consist of typical calc-alkaline, medium-K rocks, similar to the volcanic rocks which outcrop in the same areas. The K-Ar age determinations on whole-rock samples of intrusions yielded ages between 11.9 Ma and 7.0 Ma (from Late Sarmatian to Middle Pannonian). The results are in good agreement with the common assumption, based on the biostratigraphic and geological data, that large volumes of intrusions have formed during the paroxysm of the intermediate volcanic activity in the OG. Except for the Firiza basalt intrusive complex of the Gutâi Mts (8.1-7.0 Ma), the OG intrusions show similar K-Ar ages as the intrusions of the "Subvolcanic Zone" and Călimani Mts from Eastern Carpathians. The timing of the OG intrusive magmatism partially overlaps with the timing of the intrusive magmatic activity in the Eastern Moravia and Pieniny Mts. The systematic radiometric datings in the whole OG give clear evidence that the hydrothermal activity related to the epithermal systems always postdates intrusion emplacement.

  9. Dynamically adaptive data-driven simulation of extreme hydrological flows

    Science.gov (United States)

    Kumar Jain, Pushkar; Mandli, Kyle; Hoteit, Ibrahim; Knio, Omar; Dawson, Clint

    2018-02-01

    Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

  10. Dynamically adaptive data-driven simulation of extreme hydrological flows

    KAUST Repository

    Kumar Jain, Pushkar

    2017-12-27

    Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

  11. Computer Adaptive Testing, Big Data and Algorithmic Approaches to Education

    Science.gov (United States)

    Thompson, Greg

    2017-01-01

    This article critically considers the promise of computer adaptive testing (CAT) and digital data to provide better and quicker data that will improve the quality, efficiency and effectiveness of schooling. In particular, it uses the case of the Australian NAPLAN test that will become an online, adaptive test from 2016. The article argues that…

  12. On complex adaptive systems and terrorism

    International Nuclear Information System (INIS)

    Ahmed, E.; Elgazzar, A.S.; Hegazi, A.S.

    2005-01-01

    Complex adaptive systems (CAS) are ubiquitous in nature. They are basic in social sciences. An overview of CAS is given with emphasize on the occurrence of bad side effects to seemingly 'wise' decisions. Hence application to terrorism is given. Some conclusions on how to deal with this phenomena are proposed

  13. Data-Driven Adaptive Observer for Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Shen Yin

    2012-01-01

    Full Text Available This paper presents an approach for data-driven design of fault diagnosis system. The proposed fault diagnosis scheme consists of an adaptive residual generator and a bank of isolation observers, whose parameters are directly identified from the process data without identification of complete process model. To deal with normal variations in the process, the parameters of residual generator are online updated by standard adaptive technique to achieve reliable fault detection performance. After a fault is successfully detected, the isolation scheme will be activated, in which each isolation observer serves as an indicator corresponding to occurrence of a particular type of fault in the process. The thresholds can be determined analytically or through estimating the probability density function of related variables. To illustrate the performance of proposed fault diagnosis approach, a laboratory-scale three-tank system is finally utilized. It shows that the proposed data-driven scheme is efficient to deal with applications, whose analytical process models are unavailable. Especially, for the large-scale plants, whose physical models are generally difficult to be established, the proposed approach may offer an effective alternative solution for process monitoring.

  14. Building an intrusion detection system using a filter-based feature selection algorithm

    NARCIS (Netherlands)

    Ambusaidi, Mohammed A.; He, Xiangjian; Nanda, Priyadarsi; Tan, Zhiyuan

    2016-01-01

    Redundant and irrelevant features in data have caused a long-term problem in network traffic classification. These features not only slow down the process of classification but also prevent a classifier from making accurate decisions, especially when coping with big data. In this paper, we propose a

  15. Clumped isotopes complement petrological data in the investigation of contact metamorphic aureoles: a case study from the Middle Triassic Monzoni intrusion (Northern Italy)

    Science.gov (United States)

    Müller, Inigo Andreas; Storck, Julian-Christopher; Brack, Peter; Bernasconi, Stefano M.

    2017-04-01

    Carbonate clumped isotope thermometry is a technique which measures the abundance of the 13C-18O-16O2 isotopologue in carbonate rocks. Its abundance is solely dependent on the formation temperature of the carbonate minerals, which makes this still novel method very attractive for research on paleoclimate or low temperature diagenetic processes. If carbonate rocks are exposed to high temperatures as during contact metamorphism or deep burial, the clumped isotope thermometer suffers from solid state reordering, destroying the primary temperature signal. However, this does not mean clumped isotopes cannot be applied on carbonates that were heated in high temperature regimes. In contrast it offers a great tool to track the extent a carbonate was heated and reveal secondary carbonate precipitation due to alteration by circulating fluids. We used carbonates from the contact aureole of the Monzoni intrusion in northern Italy to test the application of clumped isotopes in such an extreme environment. Our measurements show that solid state reordering of the clumped isotope signature and thus an increased temperature signal occurred already 3 km distal from the contact. In contrast, mineral paragenesis studies can only reconstruct the strong temperature decrease within 1.5 km from the contact, whereas carbonates exposed to temperatures below 300 °C do not form mineral assemblages allowing the reconstruction of temperatures. Towards the contact of the Monzoni intrusion clumped isotope data showed again decreasing temperatures and a change in their oxygen isotope composition. This probably reflects the later stage alteration of circulating fluids and subsequent precipitation of secondary carbonates. Our findings show that clumped isotopes are a powerful tool to estimate the extent of contact metamorphism in the cooler part of the aureole at temperatures up to 300 °C. Clumped isotope studies can complement petrological data in the low temperature range to improve thermal

  16. Changing Paradigms: From Schooling to Schools as Adaptive Recommendation Systems

    DEFF Research Database (Denmark)

    Christiansen, René Boyer; Gynther, Karsten; Petersen, Anne Kristine

    2017-01-01

    The paper explores a shift in education from educational systems requiring student adaptation to educational recommendation systems adapting to students’ individual needs. The paper discusses the concept of adaptation as addressed in educational research and draws on the system theory of Heinz von...... system adaptation and recommendation systems. These different understandings constitute a design framework that is used to analyze two current trends: Adaptive learning systems and learning analytics. Finally, the paper discusses the potential of looking at adaptation as recommendation systems...... Foerster to shed light on how the educational system has used and understood adaptation. In this context, we point out two different approaches to educational adaptation: 1) students adapting to the educational system and 2) the attempt of the educational system to adapt to students through automatized...

  17. Cal-Adapt: California's Climate Data Resource and Interactive Toolkit

    Science.gov (United States)

    Thomas, N.; Mukhtyar, S.; Wilhelm, S.; Galey, B.; Lehmer, E.

    2016-12-01

    Cal-Adapt is a web-based application that provides an interactive toolkit and information clearinghouse to help agencies, communities, local planners, resource managers, and the public understand climate change risks and impacts at the local level. The website offers interactive, visually compelling, and useful data visualization tools that show how climate change might affect California using downscaled continental climate data. Cal-Adapt is supporting California's Fourth Climate Change Assessment through providing access to the wealth of modeled and observed data and adaption-related information produced by California's scientific community. The site has been developed by UC Berkeley's Geospatial Innovation Facility (GIF) in collaboration with the California Energy Commission's (CEC) Research Program. The Cal-Adapt website allows decision makers, scientists and residents of California to turn research results and climate projections into effective adaptation decisions and policies. Since its release to the public in June 2011, Cal-Adapt has been visited by more than 94,000 unique visitors from over 180 countries, all 50 U.S. states, and 689 California localities. We will present several key visualizations that have been employed by Cal-Adapt's users to support their efforts to understand local impacts of climate change, indicate the breadth of data available, and delineate specific use cases. Recently, CEC and GIF have been developing and releasing Cal-Adapt 2.0, which includes updates and enhancements that are increasing its ease of use, information value, visualization tools, and data accessibility. We showcase how Cal-Adapt is evolving in response to feedback from a variety of sources to present finer-resolution downscaled data, and offer an open API that allows other organization to access Cal-Adapt climate data and build domain specific visualization and planning tools. Through a combination of locally relevant information, visualization tools, and access to

  18. Geophysical characterization from Itu intrusive suite

    International Nuclear Information System (INIS)

    Pascholati, M.E.

    1989-01-01

    The integrated use of geophysical, geological, geochemical, petrographical and remote sensing data resulted in a substantial increase in the knowledge of the Itu Intrusive Suite. The main geophysical method was gamma-ray spectrometry together with fluorimetry and autoradiography. Three methods were used for calculation of laboratory gamma-ray spectrometry data. For U, the regression method was the best one. For K and Th, equations system and absolute calibration presented the best results. Surface gamma-ray spectrometry allowed comparison with laboratory data and permitted important contribution to the study of environmental radiation. (author)

  19. Two Perspectives on Information System Adaptation

    DEFF Research Database (Denmark)

    Jensen, Tina Blegind; Kjærgaard, Annemette; Svejvig, Per

    Institutional theory has proven to be a central analytical perspective for investigating the role of larger social and historical structures of Information System (IS) adaptation. However, it does not explicitly account for how organizational actors make sense of and enact IS in their local context...... for investigating the phenomenon of IS adaptation. Furthermore, we explore a combination of the two theories with a case study in a health care setting where an Electronic Patient Record (EPR) system was introduced and used by a group of doctors. The empirical case provides evidence of how existing institutional...... structures influenced the doctors' sensemaking of the EPR system. Additionally, it illustrates how the doctors made sense of the EPR system in practice. The paper outlines that: 1) institutional theory has its explanatory power at the organizational field and organizational/group level of analysis focusing...

  20. Improving Air Force Active Network Defense Systems through an Analysis of Intrusion Detection Techniques

    National Research Council Canada - National Science Library

    Dunklee, David R

    2007-01-01

    .... The research then presents four recommendations to improve DCC operations. These include: Transition or improve the current signature-based IDS systems to include the capability to query and visualize network flows to detect malicious traffic...

  1. An innovative non-intrusive driver assistance system for vital signal monitoring.

    NARCIS (Netherlands)

    Sun, Y. & Yu, X.

    2016-01-01

    This paper describes an in-vehicle nonintrusive biopotential measurement system for driver health monitoring and fatigue detection. Previous research has found that the physiological signals including eye features, electrocardiography (ECG), electroencephalography (EEG) and their secondary

  2. Pukala intrusion, its age and connection to hydrothermal alteration in Orivesi, southwestern Finland

    Directory of Open Access Journals (Sweden)

    Matti Talikka

    2005-01-01

    Full Text Available The Pukala intrusion is situated in the Paleoproterozoic Svecofennian domain of the Fennoscandian Shield in the contact region between the Central Finland Granitoid Complex and the Tampere Belt. The acid subvolcanic intrusion, which is in contact or close to severalaltered domains, mainly consists of porphyritic granodiorite and trondhjemite. The Pukala intrusion was emplaced into volcanic sequence in an island-arc or fore-arc setting before or during the early stages of the main regional deformation phase of the Svecofennian orogeny. On the basis of the geochemical data, the Pukala intrusion is a peraluminous volcanic-arc granitoid. After crystallisation at 1896±3 Ma, multiphase deformation and metamorphismcaused alteration, recrystallisation, and orientation of the minerals, and tilted the intrusion steeply towards south. The 1851±5 Ma U-Pb age for titanite is connected to the late stages of the Svecofennian tectonometamorphic evolution of the region. Several hydrothermally altered domains are located in the felsic and intermediate metavolcanic rocks of the Tampere Belt within less than one kilometre south of the Pukala intrusion. Alteration is divided into three basic types: partial silica alteration, chlorite-sericite±silica alteration, and sericite alteration in shear zones. The first two types probably formed during the emplacement and crystallisation of the Pukala intrusion, and the third is linked to late shearing. Intense sericitisation and comb quartz bands in the contact of theintrusion and the altered domain at Kutemajärvi suggest that the hydrothermal system was driven by the Pukala intrusion.

  3. Model reference adaptive systems some examples.

    Science.gov (United States)

    Landau, I. D.; Sinner, E.; Courtiol, B.

    1972-01-01

    A direct design method is derived for several single-input single-output model reference adaptive systems (M.R.A.S.). The approach used helps to clarify the various steps involved in a design, which utilizes the hyperstability concept. An example of a multiinput, multioutput M.R.A.S. is also discussed. Attention is given to the problem of a series compensator. It is pointed out that a series compensator which contains derivative terms must generally be introduced in the adaptation mechanism in order to assure asymptotic hyperstability. Results obtained by the simulation of a M.R.A.S. on an analog computer are also presented.

  4. On the Feasibility of Intrusion Detection Inside Workstation Disks

    National Research Council Canada - National Science Library

    Griffin, John L; Pennington, Adam; Bucy, John S; Choundappan, Deepa; Muralidharan, Nithya; Ganger, Gregory R

    2003-01-01

    Storage-based intrusion detection systems (IDSs) can be valuable tools in monitoring for and notifying administrators of malicious software executing on a host computer, including many common intrusion tool kits...

  5. A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

    Science.gov (United States)

    2011-03-01

    such as a worldwide corporation , government agency, or military. Therefore, the network of interest to this research is the Autonomous System (AS)-level...section. Meadows’ research is concerned with large and sometimes abstract systems, including corporations , economies, living organisms, cities, and...Framework for Developing Multi-Objective Op- timization Metaheuristics. Technical Report ITI-2006-10, Departamento de Lenguajes y Ciencias de la

  6. Adaptable Transponder for Multiple Telemetry Systems

    Science.gov (United States)

    Sims, William Herbert, III (Inventor); Varnavas, Kosta A. (Inventor)

    2014-01-01

    The present invention is a stackable telemetry circuit board for use in telemetry systems for satellites and other purposes. The present invention incorporates previously-qualified interchangeable circuit boards, or "decks," that perform functions such as power, signal receiving and transmission, and processing. Each deck is adapted to serve a range of telemetry applications. This provides flexibility in the construction of the stackable telemetry circuit board and significantly reduces the cost and time necessary to develop a telemetry system.

  7. Surface Operations Data Analysis and Adaptation Tool, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — This effort undertook the creation of a Surface Operations Data Analysis and Adaptation (SODAA) tool to store data relevant to airport surface research and...

  8. SDR implementation of the receiver of adaptive communication system

    Science.gov (United States)

    Skarzynski, Jacek; Darmetko, Marcin; Kozlowski, Sebastian; Kurek, Krzysztof

    2016-04-01

    The paper presents software implementation of a receiver forming a part of an adaptive communication system. The system is intended for communication with a satellite placed in a low Earth orbit (LEO). The ability of adaptation is believed to increase the total amount of data transmitted from the satellite to the ground station. Depending on the signal-to-noise ratio (SNR) of the received signal, adaptive transmission is realized using different transmission modes, i.e., different modulation schemes (BPSK, QPSK, 8-PSK, and 16-APSK) and different convolutional code rates (1/2, 2/3, 3/4, 5/6, and 7/8). The receiver consists of a software-defined radio (SDR) module (National Instruments USRP-2920) and a multithread reception software running on Windows operating system. In order to increase the speed of signal processing, the software takes advantage of single instruction multiple data instructions supported by x86 processor architecture.

  9. Intrusion detection using pattern recognition methods

    Science.gov (United States)

    Jiang, Nan; Yu, Li

    2007-09-01

    Today, cyber attacks such as worms, scanning, active attackers are pervasive in Internet. A number of security approaches are proposed to address this problem, among which the intrusion detection system (IDS) appears to be one of the major and most effective solutions for defending against malicious users. Essentially, intrusion detection problem can be generalized as a classification problem, whose goal is to distinguish normal behaviors and anomalies. There are many well-known pattern recognition algorithms for classification purpose. In this paper we describe the details of applying pattern recognition methods to the intrusion detection research field. Experimenting on the KDDCUP 99 data set, we first use information gain metric to reduce the dimensionality of the original feature space. Two supervised methods, the support vector machine as well as the multi-layer neural network have been tested and the results display high detection rate and low false alarm rate, which is promising for real world applications. In addition, three unsupervised methods, Single-Linkage, K-Means, and CLIQUE, are also implemented and evaluated in the paper. The low computational complexity reveals their application in initial data reduction process.

  10. SWIBANGLA: Managing salt water intrusion impacts in coastal groundwater systems of Bangladesh

    NARCIS (Netherlands)

    Faneca Sànchez, Marta; Bashar, Khairul; Janssen, Gijs; Vogels, Marjolein; Snel, Jan; Zhou, Yangxiao; Stuurman, Roelof J.; Oude Essink, Gualbert

    Bangladesh is densely populated and it is expected that the population increases significantly in the coming decade, up to 60% more by 2050 according to IIASA (2013). Demand for drinking water will increase accordingly. These developments may cause significant changes in the hydrological system,

  11. Characterizing and Managing Intrusion Detection System (IDS) Alerts with Multi-Server/Multi-Priority Queuing Theory

    Science.gov (United States)

    2014-12-26

    queue (shown in green) (Reed, 1995). ....................................................................... 17 Figure 4. Class diagram depicting how...the Main Script of the model orchestrates between the three classes to create a functioning queuing system...Unlike antivirus definitions where a growing database is of little concern due to the discrete and slow arrival times of new files, IDS rule-sets

  12. Attacks against intrusion detection networks: evasion, reverse engineering and optimal countermeasures

    OpenAIRE

    Pastrana Portillo, Sergio

    2016-01-01

    Intrusion Detection Networks (IDNs) constitute a primary element in current cyberdefense systems. IDNs are composed of different nodes distributed among a network infrastructure, performing functions such as local detection --mostly by Intrusion Detection Systems (IDS) --, information sharing with other nodes in the IDN, and aggregation and correlation of data from different sources. Overall, they are able to detect distributed attacks taking place at large scale or in different parts of the ...

  13. Water System Adaptation To Hydrological Changes: Module 11, Methods and Tools: Computational Models

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  14. Water System Adaptation To Hydrological Changes: Module 8, Regulatory Framework Intersections: Past, Present, and Future

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  15. Adaptive traffic control systems for urban networks

    Directory of Open Access Journals (Sweden)

    Radivojević Danilo

    2017-01-01

    Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.

  16. A neural systems analysis of adaptive navigation.

    Science.gov (United States)

    Mizumori, S J; Cooper, B G; Leutgeb, S; Pratt, W E

    2000-01-01

    In the field of the neurobiology of learning, significant emphasis has been placed on understanding neural plasticity within a single structure (or synapse type) as it relates to a particular type of learning mediated by a particular brain area. To appreciate fully the breadth of the plasticity responsible for complex learning phenomena, it is imperative that we also examine the neural mechanisms of the behavioral instantiation of learned information, how motivational systems interact, and how past memories affect the learning process. To address this issue, we describe a model of complex learning (rodent adaptive navigation) that could be used to study dynamically interactive neural systems. Adaptive navigation depends on the efficient integration of external and internal sensory information with motivational systems to arrive at the most effective cognitive and/or behavioral strategies. We present evidence consistent with the view that during navigation: 1) the limbic thalamus and limbic cortex is primarily responsible for the integration of current and expected sensory information, 2) the hippocampal-septal-hypothalamic system provides a mechanism whereby motivational perspectives bias sensory processing, and 3) the amygdala-prefrontal-striatal circuit allows animals to evaluate the expected reinforcement consequences of context-dependent behavioral responses. Although much remains to be determined regarding the nature of the interactions among neural systems, new insights have emerged regarding the mechanisms that underlie flexible and adaptive behavioral responses.

  17. A minimally intrusive monitoring system that utilizes electricity consumption as a proxy for wellbeing

    Directory of Open Access Journals (Sweden)

    Tim D. Hunt

    Full Text Available The purpose of this work was to test the hypothesis: \\'Off-the-shelf domestic electricity meters can be utilised to assist in monitoring the wellbeing of elderly people\\'. Many studies have shown that it is, in theory, possible to use domestic electricity consumption to determine \\'activities of daily living\\' but the availability of systems for actual use is very limited. This work followed the Design Science Research Methodology to create a Java application running on the Google App Engine cloud service that interfaced with both electricity meters and voice and text services. The system was implemented and tested over a three month period with one older person and their carer. Results demonstrated that the technology readily succeeds in meeting the study\\'s initial objectives. The need for more sophisticated decision logic was apparent and a method to determine whether a home is currently occupied is likely to improve the ability to create more timely alerts.

  18. Front-end data processing the SLD data acquisition system

    International Nuclear Information System (INIS)

    Nielsen, B.S.

    1986-07-01

    The data acquisition system for the SLD detector will make extensive use of parallel at the front-end level. Fastbus acquisition modules are being built with powerful processing capabilities for calibration, data reduction and further pre-processing of the large amount of analog data handled by each module. This paper describes the read-out electronics chain and data pre-processing system adapted for most of the detector channels, exemplified by the central drift chamber waveform digitization and processing system

  19. Intelligent Adaptation Process for Case Based Systems

    International Nuclear Information System (INIS)

    Nassar, A.M.; Mohamed, A.H.; Mohamed, A.H.

    2014-01-01

    Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world. The effectiveness of any CBR system based on the quality of the storage cases in the case library. Similar cases can be retrieved and adapted to produce the solution for the new problem. One of the main issues faced the CBR systems is the difficulties of achieving the useful cases. The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library. Also, it can optimize the best one to be stored in the library for the future uses. However, the proposed system can avoid the problems of the uncertain and noisy cases. Besides, it can simply the retrieving and adaptation processes. So, it can improve the performance of the CBR system. The suggested system can be applied for many real-time problems. It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study. The proposed system has proved its performance in this field

  20. Occurrence of seawater intrusion overshoot

    NARCIS (Netherlands)

    Morgan, L.K.; Bakker, M.; Werner, A.D.

    2015-01-01

    A number of numerical modeling studies of transient sea level rise (SLR) and seawater intrusion (SI) in flux-controlled aquifer systems have reported an overshoot phenomenon, whereby the freshwater-saltwater interface temporarily extends further inland than the eventual steady state position.

  1. Distributed adaptive diagnosis of sensor faults using structural response data

    Science.gov (United States)

    Dragos, Kosmas; Smarsly, Kay

    2016-10-01

    The reliability and consistency of wireless structural health monitoring (SHM) systems can be compromised by sensor faults, leading to miscalibrations, corrupted data, or even data loss. Several research approaches towards fault diagnosis, referred to as ‘analytical redundancy’, have been proposed that analyze the correlations between different sensor outputs. In wireless SHM, most analytical redundancy approaches require centralized data storage on a server for data analysis, while other approaches exploit the on-board computing capabilities of wireless sensor nodes, analyzing the raw sensor data directly on board. However, using raw sensor data poses an operational constraint due to the limited power resources of wireless sensor nodes. In this paper, a new distributed autonomous approach towards sensor fault diagnosis based on processed structural response data is presented. The inherent correlations among Fourier amplitudes of acceleration response data, at peaks corresponding to the eigenfrequencies of the structure, are used for diagnosis of abnormal sensor outputs at a given structural condition. Representing an entirely data-driven analytical redundancy approach that does not require any a priori knowledge of the monitored structure or of the SHM system, artificial neural networks (ANN) are embedded into the sensor nodes enabling cooperative fault diagnosis in a fully decentralized manner. The distributed analytical redundancy approach is implemented into a wireless SHM system and validated in laboratory experiments, demonstrating the ability of wireless sensor nodes to self-diagnose sensor faults accurately and efficiently with minimal data traffic. Besides enabling distributed autonomous fault diagnosis, the embedded ANNs are able to adapt to the actual condition of the structure, thus ensuring accurate and efficient fault diagnosis even in case of structural changes.

  2. An Approach for Cross-Domain Intrusion Detection

    Science.gov (United States)

    2012-01-01

    supported by open source software (i.e., BASE, snort, PostgreSQL and pgpool-II). Our prototype enables an analyst to view and manipulate network trace data...multilevel (trusted) components, supported by open source software (i.e., BASE, snort, PostgreSQL and pgpool-II). Our prototype enables an analyst to view...component is implemented by the open source object-relational database system PostgreSQL 0). 4.4.3 Intrusion analysis engine The intrusion analysis

  3. Adaptive Distributed Data Structure Management for Parallel CFD Applications

    KAUST Repository

    Frisch, Jerome

    2013-09-01

    Computational fluid dynamics (CFD) simulations require a lot of computing resources in terms of CPU time and memory in order to compute with a reasonable physical accuracy. If only uniformly refined domains are applied, the amount of computing cells is growing rather fast if a certain small resolution is physically required. This can be remedied by applying adaptively refined grids. Unfortunately, due to the adaptive refinement procedures, errors are introduced which have to be taken into account. This paper is focussing on implementation details of the applied adaptive data structure management and a qualitative analysis of the introduced errors by analysing a Poisson problem on the given data structure, which has to be solved in every time step of a CFD analysis. Furthermore an adaptive CFD benchmark example is computed, showing the benefits of an adaptive refinement as well as measurements of parallel data distribution and performance. © 2013 IEEE.

  4. Water System Adaptation To Hydrological Changes: Module 9, Water System Resilience and Security under Hydrologic Variability and Uncertainty

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  5. Understanding Supply Networks from Complex Adaptive Systems

    Directory of Open Access Journals (Sweden)

    Jamur Johnas Marchi

    2014-10-01

    Full Text Available This theoretical paper is based on complex adaptive systems (CAS that integrate dynamic and holistic elements, aiming to discuss supply networks as complex systems and their dynamic and co-evolutionary processes. The CAS approach can give clues to understand the dynamic nature and co-evolution of supply networks because it consists of an approach that incorporates systems and complexity. This paper’s overall contribution is to reinforce the theoretical discussion of studies that have addressed supply chain issues, such as CAS.

  6. Orthodontic treatment of gummy smile by maxillary total intrusion with a midpalatal absolute anchorage system.

    Science.gov (United States)

    Hong, Ryoon-Ki; Lim, Seung-Min; Heo, Jung-Min; Baek, Seung-Hak

    2013-06-01

    This article describes the orthodontic treatment of a 31-year-old Korean female patient with gummy smile and crowding. The patient showed excessive gingival display in both the anterior and posterior areas and a large difference in gingival heights between the anterior and posterior teeth in the maxilla. To correct the gummy smile, we elected to intrude the entire maxillary dentition instead of focusing only on the maxillary anterior teeth. Alignment and leveling were performed, and a midpalatal absolute anchorage system as well as a modified lingual arch was designed to achieve posterosuperior movement of the entire upper dentition. The active treatment period was 18 months. The gummy smile and crowding were corrected, and the results were stable at 21 months post-treatment.

  7. Check valve slam caused by air intrusion in emergency cooling water system

    International Nuclear Information System (INIS)

    Martin, C.S.

    2011-01-01

    Waterhammer pressures were experienced during periodic starting of Residual Heat Removal (RHR) pumps at a nuclear plant. Prior to an analytical investigation careful analysis performed by plant engineers indicated that the spring effect of entrapped air in a heat exchanger resulted in water hammer due to check valve slam following flow reversal. In order to determine in more detail the values of pertinent parameters controlling this water hammer a hydraulic transient analysis was performed of the RHR piping system, including essential elements such as the pump, check valve, and heat exchanger. Using characteristic torque and pressure loss curves the motion of the check valve was determined. By comparing output of the water hammer analysis with site recordings of pump discharge pressure the computer model was calibrated, allowing for a realistic estimate of the quantity of entrapped air in the heat exchanger. (author)

  8. Adaptive optics system application for solar telescope

    Science.gov (United States)

    Lukin, V. P.; Grigor'ev, V. M.; Antoshkin, L. V.; Botugina, N. N.; Emaleev, O. N.; Konyaev, P. A.; Kovadlo, P. G.; Krivolutskiy, N. P.; Lavrionova, L. N.; Skomorovski, V. I.

    2008-07-01

    The possibility of applying adaptive correction to ground-based solar astronomy is considered. Several experimental systems for image stabilization are described along with the results of their tests. Using our work along several years and world experience in solar adaptive optics (AO) we are assuming to obtain first light to the end of 2008 for the first Russian low order ANGARA solar AO system on the Big Solar Vacuum Telescope (BSVT) with 37 subapertures Shack-Hartmann wavefront sensor based of our modified correlation tracker algorithm, DALSTAR video camera, 37 elements deformable bimorph mirror, home made fast tip-tip mirror with separate correlation tracker. Too strong daytime turbulence is on the BSVT site and we are planning to obtain a partial correction for part of Sun surface image.

  9. Next generation intelligent environments ambient adaptive systems

    CERN Document Server

    Nothdurft, Florian; Heinroth, Tobias; Minker, Wolfgang

    2016-01-01

    This book covers key topics in the field of intelligent ambient adaptive systems. It focuses on the results worked out within the framework of the ATRACO (Adaptive and TRusted Ambient eCOlogies) project. The theoretical background, the developed prototypes, and the evaluated results form a fertile ground useful for the broad intelligent environments scientific community as well as for industrial interest groups. The new edition provides: Chapter authors comment on their work on ATRACO with final remarks as viewed in retrospective Each chapter has been updated with follow-up work emerging from ATRACO An extensive introduction to state-of-the-art statistical dialog management for intelligent environments Approaches are introduced on how Trust is reflected during the dialog with the system.

  10. Adaptive and non-adaptive data hiding methods for grayscale images based on modulus function

    Directory of Open Access Journals (Sweden)

    Najme Maleki

    2014-07-01

    Full Text Available This paper presents two adaptive and non-adaptive data hiding methods for grayscale images based on modulus function. Our adaptive scheme is based on the concept of human vision sensitivity, so the pixels in edge areas than to smooth areas can tolerate much more changes without making visible distortion for human eyes. In our adaptive scheme, the average differencing value of four neighborhood pixels into a block via a threshold secret key determines whether current block is located in edge or smooth area. Pixels in the edge areas are embedded by Q-bit of secret data with a larger value of Q than that of pixels placed in smooth areas. Also in this scholar, we represent one non-adaptive data hiding algorithm. Our non-adaptive scheme, via an error reduction procedure, produces a high visual quality for stego-image. The proposed schemes present several advantages. 1-of aspects the embedding capacity and visual quality of stego-image are scalable. In other words, the embedding rate as well as the image quality can be scaled for practical applications 2-the high embedding capacity with minimal visual distortion can be achieved, 3-our methods require little memory space for secret data embedding and extracting phases, 4-secret keys have used to protect of the embedded secret data. Thus, level of security is high, 5-the problem of overflow or underflow does not occur. Experimental results indicated that the proposed adaptive scheme significantly is superior to the currently existing scheme, in terms of stego-image visual quality, embedding capacity and level of security and also our non-adaptive method is better than other non-adaptive methods, in view of stego-image quality. Results show which our adaptive algorithm can resist against the RS steganalysis attack.

  11. Algorithms and data structures for adaptive multigrid elliptic solvers

    Science.gov (United States)

    Vanrosendale, J.

    1983-01-01

    Adaptive refinement and the complicated data structures required to support it are discussed. These data structures must be carefully tuned, especially in three dimensions where the time and storage requirements of algorithms are crucial. Another major issue is grid generation. The options available seem to be curvilinear fitted grids, constructed on iterative graphics systems, and unfitted Cartesian grids, which can be constructed automatically. On several grounds, including storage requirements, the second option seems preferrable for the well behaved scalar elliptic problems considered here. A variety of techniques for treatment of boundary conditions on such grids are reviewed. A new approach, which may overcome some of the difficulties encountered with previous approaches, is also presented.

  12. An improved real time image detection system for elephant intrusion along the forest border areas.

    Science.gov (United States)

    Sugumar, S J; Jayaparvathy, R

    2014-01-01

    Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent to a base station via an RF network. The received image is decomposed using Haar wavelet to obtain multilevel wavelet coefficients, with which we perform image feature extraction and similarity match between the elephant query image and the database image using image vision algorithms. A GSM message is sent to the forest officials indicating that an elephant has been detected in the forest border and is approaching human habitat. We propose an optimized distance metric to improve the image retrieval time from the database. We compare the optimized distance metric with the popular Euclidean and Manhattan distance methods. The proposed optimized distance metric retrieves more images with lesser retrieval time than the other distance metrics which makes the optimized distance method more efficient and reliable.

  13. Adaptive stimulus optimization for sensory systems neuroscience

    OpenAIRE

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system...

  14. Development and validation of a nuclear data and calculation system for Superphenix with steel reflectors; Developpement et qualification d`un formulaire adapte a superphenix avec reflecteurs

    Energy Technology Data Exchange (ETDEWEB)

    Bosq, J.Ch

    1998-11-09

    This thesis concerns the definition and the validation of the ERANOS neutronic calculation system for steel reflected fast reactors. The calculation system uses JEF2.2 evaluated nuclear data, the ECCO cell code and the BISTRO and VARIANT transport codes. After a description of the physical phenomena induced by the existence of the these sub-critical media, an inventory of the past studies related to steel reflectors is reported. A calculational scheme taking into account the important physical phenomena (strong neutronic slowing-down, presence of broad resonances of the structural materials and spatial variation of the spectrum in the reflector) is defined. This method is validated with the TRIPOLI4 reference Monte-Carlo code. The use of this upgraded calculation method for the analysis of the part of the CIRANO experimental program devoted to the study of steel reflected configurations leads to discrepancies between the calculated and measured values. These remaining discrepancies obtained for the reactivity and the fission rate traverses are due to inaccurate nuclear data for the structural materials. The adjustment of these nuclear data in order to reduce these discrepancies id demonstrated. The additional uncertainty associated to the integral parameters of interest for a nuclear reactor (reactivity and power distribution) induced by the replacement of a fertile blanket by a steel reflector is determined for the Superphenix reactor and is proved to be small. (author) 86 refs.

  15. Multiprocessor data acquisition system

    International Nuclear Information System (INIS)

    Haumann, J.R.; Crawford, R.K.

    1987-01-01

    A multiprocessor data acquisition system has been built to replace the single processor systems at the Intense Pulsed Neutron Source (IPNS) at Argonne National Laboratory. The multiprocessor system was needed to accommodate the higher data rates at IPNS brought about by improvements in the source and changes in instrument configurations. This paper describes the hardware configuration of the system and the method of task sharing and compares results to the single processor system

  16. Simulated climate adaptation in storm-water systems: Evaluating the efficiency of within-system flexibility

    Directory of Open Access Journals (Sweden)

    Adam D. McCurdy

    Full Text Available Changes in regional temperature and precipitation patterns resulting from global climate change may adversely affect the performance of long-lived infrastructure. Adaptation may be necessary to ensure that infrastructure offers consistent service and remains cost effective. But long service times and deep uncertainty associated with future climate projections make adaptation decisions especially challenging for managers. Incorporating flexibility into systems can increase their effectiveness across different climate futures but can also add significant costs. In this paper we review existing work on flexibility in climate change adaptation of infrastructure, such as robust decision-making and dynamic adaptive pathways, apply a basic typology of flexibility, and test alternative strategies for flexibility in distributed infrastructure systems comprised of multiple emplacements of a common, long-lived element: roadway culverts. Rather than treating a system of dispersed infrastructure elements as monolithic, we simulate “options flexibility” in which inherent differences in individual elements is incorporated into adaptation decisions. We use a virtual testbed of highway drainage crossing structures to examine the performance under different climate scenarios of policies that allow for multiple adaptation strategies with varying timing based on individual emplacement characteristics. Results indicate that a strategy with options flexibility informed by crossing characteristics offers a more efficient method of adaptation than do monolithic policies. In some cases this results in more cost-effective adaptation for agencies building long-lived, climate-sensitive infrastructure, even where detailed system data and analytical capacity is limited. Keywords: Climate adaptation, Stormwater management, Adaptation pathways

  17. Complex Adaptive Systems of Systems (CASOS) engineering environment.

    Energy Technology Data Exchange (ETDEWEB)

    Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

    2012-02-01

    Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

  18. STATISTICS. The reusable holdout: Preserving validity in adaptive data analysis.

    Science.gov (United States)

    Dwork, Cynthia; Feldman, Vitaly; Hardt, Moritz; Pitassi, Toniann; Reingold, Omer; Roth, Aaron

    2015-08-07

    Misapplication of statistical data analysis is a common cause of spurious discoveries in scientific research. Existing approaches to ensuring the validity of inferences drawn from data assume a fixed procedure to be performed, selected before the data are examined. In common practice, however, data analysis is an intrinsically adaptive process, with new analyses generated on the basis of data exploration, as well as the results of previous analyses on the same data. We demonstrate a new approach for addressing the challenges of adaptivity based on insights from privacy-preserving data analysis. As an application, we show how to safely reuse a holdout data set many times to validate the results of adaptively chosen analyses. Copyright © 2015, American Association for the Advancement of Science.

  19. Gaia as a complex adaptive system.

    Science.gov (United States)

    Lenton, Timothy M; van Oijen, Marcel

    2002-05-29

    We define the Gaia system of life and its environment on Earth, review the status of the Gaia theory, introduce potentially relevant concepts from complexity theory, then try to apply them to Gaia. We consider whether Gaia is a complex adaptive system (CAS) in terms of its behaviour and suggest that the system is self-organizing but does not reside in a critical state. Gaia has supported abundant life for most of the last 3.8 Gyr. Large perturbations have occasionally suppressed life but the system has always recovered without losing the capacity for large-scale free energy capture and recycling of essential elements. To illustrate how complexity theory can help us understand the emergence of planetary-scale order, we present a simple cellular automata (CA) model of the imaginary planet Daisyworld. This exhibits emergent self-regulation as a consequence of feedback coupling between life and its environment. Local spatial interaction, which was absent from the original model, can destabilize the system by generating bifurcation regimes. Variation and natural selection tend to remove this instability. With mutation in the model system, it exhibits self-organizing adaptive behaviour in its response to forcing. We close by suggesting how artificial life ('Alife') techniques may enable more comprehensive feasibility tests of Gaia.

  20. Direct adaptive control for nonlinear uncertain dynamical systems

    Science.gov (United States)

    Hayakawa, Tomohisa

    In light of the complex and highly uncertain nature of dynamical systems requiring controls, it is not surprising that reliable system models for many high performance engineering and life science applications are unavailable. In the face of such high levels of system uncertainty, robust controllers may unnecessarily sacrifice system performance whereas adaptive controllers are clearly appropriate since they can tolerate far greater system uncertainty levels to improve system performance. In this dissertation, we develop a Lyapunov-based direct adaptive and neural adaptive control framework that addresses parametric uncertainty, unstructured uncertainty, disturbance rejection, amplitude and rate saturation constraints, and digital implementation issues. Specifically, we consider the following research topics; direct adaptive control for nonlinear uncertain systems with exogenous disturbances; robust adaptive control for nonlinear uncertain systems; adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints; adaptive reduced-order dynamic compensation for nonlinear uncertain systems; direct adaptive control for nonlinear matrix second-order dynamical systems with state-dependent uncertainty; adaptive control for nonnegative and compartmental dynamical systems with applications to general anesthesia; direct adaptive control of nonnegative and compartmental dynamical systems with time delay; adaptive control for nonlinear nonnegative and compartmental dynamical systems with applications to clinical pharmacology; neural network adaptive control for nonlinear nonnegative dynamical systems; passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems; neural network adaptive dynamic output feedback control for nonlinear nonnegative systems using tapped delay memory units; Lyapunov-based adaptive control framework for discrete-time nonlinear systems with exogenous disturbances

  1. Intrusion detection techniques for plant-wide network in a nuclear power plant

    International Nuclear Information System (INIS)

    Rajasekhar, P.; Shrikhande, S.V.; Biswas, B.B.; Patil, R.K.

    2012-01-01

    Nuclear power plants have a lot of critical data to be sent to the operator workstations. A plant wide integrated communication network, with high throughput, determinism and redundancy, is required between the workstations and the field. Switched Ethernet network is a promising prospect for such an integrated communication network. But for such an integrated system, intrusion is a major issue. Hence the network should have an intrusion detection system to make the network data secure and enhance the network availability. Intrusion detection is the process of monitoring the events occurring in a network and analyzing them for signs of possible incidents, which are violations or imminent threats of violation of network security policies, acceptable user policies, or standard security practices. This paper states the various intrusion detection techniques and approaches which are applicable for analysis of a plant wide network. (author)

  2. An Adaptable Seismic Data Format for Modern Scientific Workflows

    Science.gov (United States)

    Smith, J. A.; Bozdag, E.; Krischer, L.; Lefebvre, M.; Lei, W.; Podhorszki, N.; Tromp, J.

    2013-12-01

    Data storage, exchange, and access play a critical role in modern seismology. Current seismic data formats, such as SEED, SAC, and SEG-Y, were designed with specific applications in mind and are frequently a major bottleneck in implementing efficient workflows. We propose a new modern parallel format that can be adapted for a variety of seismic workflows. The Adaptable Seismic Data Format (ASDF) features high-performance parallel read and write support and the ability to store an arbitrary number of traces of varying sizes. Provenance information is stored inside the file so that users know the origin of the data as well as the precise operations that have been applied to the waveforms. The design of the new format is based on several real-world use cases, including earthquake seismology and seismic interferometry. The metadata is based on the proven XML schemas StationXML and QuakeML. Existing time-series analysis tool-kits are easily interfaced with this new format so that seismologists can use robust, previously developed software packages, such as ObsPy and the SAC library. ADIOS, netCDF4, and HDF5 can be used as the underlying container format. At Princeton University, we have chosen to use ADIOS as the container format because it has shown superior scalability for certain applications, such as dealing with big data on HPC systems. In the context of high-performance computing, we have implemented ASDF into the global adjoint tomography workflow on Oak Ridge National Laboratory's supercomputer Titan.

  3. Towards an Empathizing and Adaptive Storyteller System

    DEFF Research Database (Denmark)

    Bae, Byung Chull; Brunete, Alberto; Malik, Usman

    2012-01-01

    This paper describes our ongoing effort to build an empathizing and adaptive storyteller system. The system under development aims to utilize emotional expressions generated from an avatar or a humanoid robot in addition to the listener’s responses which are monitored in real time, in order...... to deliver a story in an effective manner. We conducted a pilot study and the results were analyzed in two ways: first, through a survey questionnaire analysis based on the participant’s subjective ratings; second, through automated video analysis based on the participant’s emotional facial expression...

  4. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2013-01-01

    Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...

  5. An Ensemble of Adaptive Neuro-Fuzzy Kohonen Networks for Online Data Stream Fuzzy Clustering

    OpenAIRE

    Hu, Zhengbing; Bodyanskiy, Yevgeniy V.; Tyshchenko, Oleksii K.; Boiko, Olena O.

    2016-01-01

    A new approach to data stream clustering with the help of an ensemble of adaptive neuro-fuzzy systems is proposed. The proposed ensemble is formed with adaptive neuro-fuzzy self-organizing Kohonen maps in a parallel processing mode. A final result is chosen by the best neuro-fuzzy self-organizing Kohonen map.

  6. The Development of Agent Information for Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Bambang Sugiantoro

    2017-10-01

    Full Text Available As the challenges and problems surround intrusion rises rapidly, the intrusion detection system has been gradually developed. Agent-based approach for intrusion detection system has developed from single to multi agent, and later developed mobile agents in order to increase system's capability to face with a more complex challenge and change. A number of studies had been identified that mobile agent can reduce network traffic, however the study related to intrusion detection using static and mobile agent for finding intruder has not been fully achieved.Keywords:  Information, Intrusion, mobile, networks

  7. Generating Shifting Workloads to Benchmark Adaptability in Relational Database Systems

    Science.gov (United States)

    Rabl, Tilmann; Lang, Andreas; Hackl, Thomas; Sick, Bernhard; Kosch, Harald

    A large body of research concerns the adaptability of database systems. Many commercial systems already contain autonomic processes that adapt configurations as well as data structures and data organization. Yet there is virtually no possibility for a just measurement of the quality of such optimizations. While standard benchmarks have been developed that simulate real-world database applications very precisely, none of them considers variations in workloads produced by human factors. Today’s benchmarks test the performance of database systems by measuring peak performance on homogeneous request streams. Nevertheless, in systems with user interaction access patterns are constantly shifting. We present a benchmark that simulates a web information system with interaction of large user groups. It is based on the analysis of a real online eLearning management system with 15,000 users. The benchmark considers the temporal dependency of user interaction. Main focus is to measure the adaptability of a database management system according to shifting workloads. We will give details on our design approach that uses sophisticated pattern analysis and data mining techniques.

  8. Hybrid cognitive engine for radio systems adaptation

    KAUST Repository

    Alqerm, Ismail

    2017-07-20

    Network efficiency and proper utilization of its resources are essential requirements to operate wireless networks in an optimal fashion. Cognitive radio aims to fulfill these requirements by exploiting artificial intelligence techniques to create an entity called cognitive engine. Cognitive engine exploits awareness about the surrounding radio environment to optimize the use of radio resources and adapt relevant transmission parameters. In this paper, we propose a hybrid cognitive engine that employs Case Based Reasoning (CBR) and Decision Trees (DTs) to perform radio adaptation in multi-carriers wireless networks. The engine complexity is reduced by employing DTs to improve the indexing methodology used in CBR cases retrieval. The performance of our hybrid engine is validated using software defined radios implementation and simulation in multi-carrier environment. The system throughput, signal to noise and interference ratio, and packet error rate are obtained and compared with other schemes in different scenarios.

  9. Signal system data mining

    Science.gov (United States)

    2000-09-01

    Intelligent transportation systems (ITS) include large numbers of traffic sensors that collect enormous quantities of data. The data provided by ITS is necessary for advanced forms of control, however basic forms of control, primarily time-of-day (TO...

  10. Longline Observer Data System

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LODS, the Hawaii Longline Observer Data System, is a complete suite of tools designed to collect, process, and manage quality fisheries data and information. Guided...

  11. Planetary Data System (PDS)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Planetary Data System (PDS) is an archive of data products from NASA planetary missions, which is sponsored by NASA's Science Mission Directorate. We actively...

  12. Adaptive Sampling for High Throughput Data Using Similarity Measures

    Energy Technology Data Exchange (ETDEWEB)

    Bulaevskaya, V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sales, A. P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-05-06

    The need for adaptive sampling arises in the context of high throughput data because the rates of data arrival are many orders of magnitude larger than the rates at which they can be analyzed. A very fast decision must therefore be made regarding the value of each incoming observation and its inclusion in the analysis. In this report we discuss one approach to adaptive sampling, based on the new data point’s similarity to the other data points being considered for inclusion. We present preliminary results for one real and one synthetic data set.

  13. Small Aircraft Data Distribution System

    Science.gov (United States)

    Chazanoff, Seth L.; Dinardo, Steven J.

    2012-01-01

    The CARVE Small Aircraft Data Distribution System acquires the aircraft location and attitude data that is required by the various programs running on a distributed network. This system distributes the data it acquires to the data acquisition programs for inclusion in their data files. It uses UDP (User Datagram Protocol) to broadcast data over a LAN (Local Area Network) to any programs that might have a use for the data. The program is easily adaptable to acquire additional data and log that data to disk. The current version also drives displays using precision pitch and roll information to aid the pilot in maintaining a level-level attitude for radar/radiometer mapping beyond the degree available by flying visually or using a standard gyro-driven attitude indicator. The software is designed to acquire an array of data to help the mission manager make real-time decisions as to the effectiveness of the flight. This data is displayed for the mission manager and broadcast to the other experiments on the aircraft for inclusion in their data files. The program also drives real-time precision pitch and roll displays for the pilot and copilot to aid them in maintaining the desired attitude, when required, during data acquisition on mapping lines.

  14. Scoping calculation of nuclides migration in engineering barrier system for effect of volume expansion due to overpack corrosion and intrusion of the buffer material

    Energy Technology Data Exchange (ETDEWEB)

    Yoshita, Takashi; Ishihara, Yoshinao; Ishiguro, Katsuhiko; Ohi, Takao [Waste Isolation Research Division, Waste Management and Fuel Cycle Research Center, Tokai Works, Japan Nuclear Cycle Development Inst., Tokai, Ibaraki (Japan); Nakajima, Kunihiko [Nuclear Energy System Incorporated, Tokyo (Japan)

    1999-11-01

    Corrosion of the carbon steel overpack leads to a volume expansion since the specific gravity of corrosion products is smaller than carbon steel. The buffer material is compressed due to the corrosive swelling, reducing its thickness and porosity. On the other hand, buffer material may be extruded into fractures of the surrounding rock and this may lead to a deterioration of the planned functions of the buffer, including retardation of nuclides migration and colloid filtration. In this study, the sensitivity analyses for the effect of volume expansion and intrusion of the buffer material on nuclide migration in the engineering barrier system are carried out. The sensitivity analyses were performed on the decrease in the thickness of the buffer material in the radial direction caused by the corrosive swelling, and the change in the porosity and dry density of the buffer caused by both compacting due to corrosive swelling and intrusion of buffer material. As results, it was found the maximum release rates of relatively shorter half-life nuclides from the outside of the buffer material decreased for taking into account of a volume expansion due to overpack corrosion. On the other hand, the maximum release rates increased when the intrusion of buffer material was also taking into account. It was, however, the maximum release rates of longer half-life nuclides, such as Cs-137 and Np-237, were insensitive to the change of buffer material thickness, and porosity and dry density of buffer. (author)

  15. DIRAC Data Management System

    CERN Document Server

    Smith, A C

    2007-01-01

    The LHCb experiment being built to utilize CERN’s flagship Large Hadron Collider will generate data to be analysed by a community of over 600 physicists worldwide. DIRAC, LHCb’s Workload and Data Management System, facilitates the use of underlying EGEE Grid resources to generate, process and analyse this data in the distributed environment. The Data Management System, presented here, provides real-time, data-driven distribution in accordance with LHCb’s Computing Model. The data volumes produced by the LHC experiments are unprecedented, rendering individual institutes and even countries, unable to provide the computing and storage resources required to make full use of the produced data. EGEE Grid resources allow the processing of LHCb data possible in a distributed fashion and LHCb’s Computing Model is based on this approach. Data Management in this environment requires reliable and high-throughput transfer of data, homogeneous access to storage resources and the cataloguing of data replicas, all of...

  16. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2015-01-01

    This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...

  17. Adaptive Sensing Based on Profiles for Sensor Systems

    Directory of Open Access Journals (Sweden)

    Yoshiteru Ishida

    2009-10-01

    Full Text Available This paper proposes a profile-based sensing framework for adaptive sensor systems based on models that relate possibly heterogeneous sensor data and profiles generated by the models to detect events. With these concepts, three phases for building the sensor systems are extracted from two examples: a combustion control sensor system for an automobile engine, and a sensor system for home security. The three phases are: modeling, profiling, and managing trade-offs. Designing and building a sensor system involves mapping the signals to a model to achieve a given mission.

  18. Water System Adaptation To Hydrological Changes: Module 5, Water Quality and Infrastructure Response to Rapid Urbanization: Adaptation Case Study in China

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  19. TOPEX ground data system

    Science.gov (United States)

    Rosell, S. N.; Yamarone, C. A., Jr.

    The TOPEX Project is a proposed oceanographic mission to measure the topography of the sea surface for a period of three years. This mission is sponsored by the National Aeronautics and Space Administration and managed by the Jet Propulsion Laboratory. Measurements of topography are used to study ocean currents, tides, bathymetry and the oceanic geoid. Several of the primary goals of this mission are to process and verify the altimetric data, and distribute them within days to the science investigators. This paper describes the TOPEX end-to-end ground data system. In addition to controlling the TOPEX satellite, the ground data system has been designed to minimize the time from data acquisition to science processing and data distribution. A centralized design supports the favorable response time of the system and also allows for operational efficiencies. Networking of real time and non-real time elements of the data system provides for more effective data processing.

  20. Cross-bandwidth adaptation for ASR systems

    CSIR Research Space (South Africa)

    Kleynhans, N

    2013-12-01

    Full Text Available Mismatches between application and training data greatly reduce the performance of automatic speech recognition (ASR) systems. However, collecting suitable amounts of in-domain and application-specific data for training is resource intensive and may...

  1. Adaptive Ensemble with Human Memorizing Characteristics for Data Stream Mining

    Directory of Open Access Journals (Sweden)

    Yanhuang Jiang

    2015-01-01

    Full Text Available Combining several classifiers on sequential chunks of training instances is a popular strategy for data stream mining with concept drifts. This paper introduces human recalling and forgetting mechanisms into a data stream mining system and proposes a Memorizing Based Data Stream Mining (MDSM model. In this model, each component classifier is regarded as a piece of knowledge that a human obtains through learning some materials and has a memory retention value reflecting its usefulness in the history. The classifiers with high memory retention values are reserved in a “knowledge repository.” When a new data chunk comes, most useful classifiers will be selected (recalled from the repository and compose the current target ensemble. Based on MDSM, we put forward a new algorithm, MAE (Memorizing Based Adaptive Ensemble, which uses Ebbinghaus forgetting curve as the forgetting mechanism and adopts ensemble pruning as the recalling mechanism. Compared with four popular data stream mining approaches on the datasets with different concept drifts, the experimental results show that MAE achieves high and stable predicting accuracy, especially for the applications with recurring or complex concept drifts. The results also prove the effectiveness of MDSM model.

  2. Data adaptive estimation of transversal blood flow velocities

    DEFF Research Database (Denmark)

    Pirnia, E.; Jakobsson, A.; Gudmundson, E.

    2014-01-01

    The examination of blood flow inside the body may yield important information about vascular anomalies, such as possible indications of, for example, stenosis. Current Medical ultrasound systems suffer from only allowing for measuring the blood flow velocity along the direction of irradiation......, posing natural difficulties due to the complex behaviour of blood flow, and due to the natural orientation of most blood vessels. Recently, a transversal modulation scheme was introduced to induce also an oscillation along the transversal direction, thereby allowing for the measurement of also...... the transversal blood flow. In this paper, we propose a novel data-adaptive blood flow estimator exploiting this modulation scheme. Using realistic Field II simulations, the proposed estimator is shown to achieve a notable performance improvement as compared to current state-of-the-art techniques....

  3. Multiresolution Analysis Adapted to Irregularly Spaced Data

    Directory of Open Access Journals (Sweden)

    Anissa Mokraoui

    2009-01-01

    Full Text Available This paper investigates the mathematical background of multiresolution analysis in the specific context where the signal is represented by irregularly sampled data at known locations. The study is related to the construction of nested piecewise polynomial multiresolution spaces represented by their corresponding orthonormal bases. Using simple spline basis orthonormalization procedures involves the construction of a large family of orthonormal spline scaling bases defined on consecutive bounded intervals. However, if no more additional conditions than those coming from multiresolution are imposed on each bounded interval, the orthonormal basis is represented by a set of discontinuous scaling functions. The spline wavelet basis also has the same problem. Moreover, the dimension of the corresponding wavelet basis increases with the spline degree. An appropriate orthonormalization procedure of the basic spline space basis, whatever the degree of the spline, allows us to (i provide continuous scaling and wavelet functions, (ii reduce the number of wavelets to only one, and (iii reduce the complexity of the filter bank. Examples of the multiresolution implementations illustrate that the main important features of the traditional multiresolution are also satisfied.

  4. Online data processing system

    International Nuclear Information System (INIS)

    Nakahara, Yoshinori; Yagi, Hideyuki; Yamada, Takayuki

    1979-02-01

    A pulse height analyzer terminal system PHATS has been developed for online data processing via JAERI-TOKAI computer network. The system is controled by using a micro-computer MICRO-8 which was developed for the JAERI-TOKAI network. The system program consists of two subprograms, online control system ONLCS and pulse height analyzer control system PHACS. ONLCS links the terminal with the conversational programming system of FACOM 230/75 through the JAERI-TOKAI network and controls data processing in TSS and remote batch modes. PHACS is used to control INPUT/OUTPUT of data between pulse height analyzer and cassette-MT or typewriter. This report describes the hardware configuration and the system program in detail. In the appendix, explained are real time monitor, type of message, PEX to PEX protocol and Host to Host protocol, required for the system programming. (author)

  5. Smarter Earth Science Data System

    Science.gov (United States)

    Huang, Thomas

    2013-01-01

    The explosive growth in Earth observational data in the recent decade demands a better method of interoperability across heterogeneous systems. The Earth science data system community has mastered the art in storing large volume of observational data, but it is still unclear how this traditional method scale over time as we are entering the age of Big Data. Indexed search solutions such as Apache Solr (Smiley and Pugh, 2011) provides fast, scalable search via keyword or phases without any reasoning or inference. The modern search solutions such as Googles Knowledge Graph (Singhal, 2012) and Microsoft Bing, all utilize semantic reasoning to improve its accuracy in searches. The Earth science user community is demanding for an intelligent solution to help them finding the right data for their researches. The Ontological System for Context Artifacts and Resources (OSCAR) (Huang et al., 2012), was created in response to the DARPA Adaptive Vehicle Make (AVM) programs need for an intelligent context models management system to empower its terrain simulation subsystem. The core component of OSCAR is the Environmental Context Ontology (ECO) is built using the Semantic Web for Earth and Environmental Terminology (SWEET) (Raskin and Pan, 2005). This paper presents the current data archival methodology within a NASA Earth science data centers and discuss using semantic web to improve the way we capture and serve data to our users.

  6. MPS Data Acquisition System

    International Nuclear Information System (INIS)

    Eiseman, S.E.; Miller, W.J.

    1975-01-01

    A description is given of the data acquisition system used with the multiparticle spectrometer facility at Brookhaven. Detailed information is provided on that part of the system which connects the detectors to the data handler; namely, the detector electronics, device controller, and device port optical isolator

  7. Adaptive stimulus optimization for sensory systems neuroscience.

    Science.gov (United States)

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.

  8. Adaptive Sliding Mode Observer for a Class of Systems

    OpenAIRE

    D.Elleuch; T.Damak

    2010-01-01

    In this paper, the performance of two adaptive observers applied to interconnected systems is studied. The nonlinearity of systems can be written in a fractional form. The first adaptive observer is an adaptive sliding mode observer for a Lipchitz nonlinear system and the second one is an adaptive sliding mode observer having a filtered error as a sliding surface. After comparing their performances throughout the inverted pendulum mounted on a car system, it was shown tha...

  9. Adaptive fingerprint image enhancement with emphasis on preprocessing of data.

    Science.gov (United States)

    Bartůnek, Josef Ström; Nilsson, Mikael; Sällberg, Benny; Claesson, Ingvar

    2013-02-01

    This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are: 1) preprocessing; 2) global analysis; 3) local analysis; and 4) matched filtering. In the preprocessing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated toward the NIST developed NBIS software for fingerprint recognition on FVC databases.

  10. Scaling of Adaptive Immune System Repertoires

    Science.gov (United States)

    Sethna, Zachary; Elhanati, Yuval; Callan, Curtis

    The adaptive immune system has evolved a stochastic method called VDJ recombination for the purpose of generating the necessary receptor diversity to identify all foreign pathogens. Recent work characterizing the probability distributions of this VDJ recombination process in mouse and human T-cell repertoires shows a massive difference in the corresponding diversities. The increased diversity of the human repertoire is wholly driven by an increase in the average number of nucleotide insertions in VDJ recombination. In this talk the impact of different insertion profiles is quantified and a model for the scaling of such repertoires with respect to the size of the repertoire is laid out.

  11. ADAPTATION TO POVERTY IN LONG-RUN PANEL DATA.

    Science.gov (United States)

    Clark, Andrew E; D'Ambrosio, Conchita; Ghislandi, Simone

    2016-07-01

    We consider the link between poverty and subjective well-being and focus in particular on potential adaptation to poverty. We use panel data on almost 54,000 individuals living in Germany from 1985 to 2012 to show, first, that life satisfaction falls with both the incidence and intensity of contemporaneous poverty. We then reveal that there is little evidence of adaptation within a poverty spell: poverty starts bad and stays bad in terms of subjective well-being. We cannot identify any cause of poverty entry that explains the overall lack of poverty adaptation.

  12. Intrusion Detection Architecture Utilizing Graphics Processors

    Directory of Open Access Journals (Sweden)

    Branislav Madoš

    2012-12-01

    Full Text Available With the thriving technology and the great increase in the usage of computer networks, the risk of having these network to be under attacks have been increased. Number of techniques have been created and designed to help in detecting and/or preventing such attacks. One common technique is the use of Intrusion Detection Systems (IDS. Today, number of open sources and commercial IDS are available to match enterprises requirements. However, the performance of these systems is still the main concern. This paper examines perceptions of intrusion detection architecture implementation, resulting from the use of graphics processor. It discusses recent research activities, developments and problems of operating systems security. Some exploratory evidence is presented that shows capabilities of using graphical processors and intrusion detection systems. The focus is on how knowledge experienced throughout the graphics processor inclusion has played out in the design of intrusion detection architecture that is seen as an opportunity to strengthen research expertise.

  13. Managing Schools as Complex Adaptive Systems: A Strategic Perspective

    Science.gov (United States)

    Fidan, Tuncer; Balci, Ali

    2017-01-01

    This conceptual study examines the analogies between schools and complex adaptive systems and identifies strategies used to manage schools as complex adaptive systems. Complex adaptive systems approach, introduced by the complexity theory, requires school administrators to develop new skills and strategies to realize their agendas in an…

  14. The Adaptive Immune System of Haloferax volcanii

    Directory of Open Access Journals (Sweden)

    Lisa-Katharina Maier

    2015-02-01

    Full Text Available To fight off invading genetic elements, prokaryotes have developed an elaborate defence system that is both adaptable and heritable—the CRISPR-Cas system (CRISPR is short for: clustered regularly interspaced short palindromic repeats and Cas: CRISPR associated. Comprised of proteins and multiple small RNAs, this prokaryotic defence system is present in 90% of archaeal and 40% of bacterial species, and enables foreign intruders to be eliminated in a sequence-specific manner. There are three major types (I–III and at least 14 subtypes of this system, with only some of the subtypes having been analysed in detail, and many aspects of the defence reaction remaining to be elucidated. Few archaeal examples have so far been analysed. Here we summarize the characteristics of the CRISPR-Cas system of Haloferax volcanii, an extremely halophilic archaeon originally isolated from the Dead Sea. It carries a single CRISPR-Cas system of type I-B, with a Cascade like complex composed of Cas proteins Cas5, Cas6b and Cas7. Cas6b is essential for CRISPR RNA (crRNA maturation but is otherwise not required for the defence reaction. A systematic search revealed that six protospacer adjacent motif (PAM sequences are recognised by the Haloferax defence system. For successful invader recognition, a non-contiguous seed sequence of 10 base-pairs between the crRNA and the invader is required.

  15. Adaptive frequency decomposition of EEG with subsequent expert system analysis.

    Science.gov (United States)

    Herrmann, C S; Arnold, T; Visbeck, A; Hundemer, H P; Hopf, H C

    2001-11-01

    We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time-frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated by the neurologist to evaluate the extracted EEG features. The system detects artefacts, describes alpha rhythm by frequency, amplitude, and stability and after artefact rejection detects pathologic slow activity. All results are displayed as linguistic terms, numerical values and maps of temporal extent, giving an overview about the clinical routine EEG.

  16. Data management in the mission data system

    Science.gov (United States)

    Wagner, David A.

    2005-01-01

    As spacecraft evolve from simple embedded devices to become more sophisticated computing platforms with complex behaviors it is increasingly necessary to model and manage the flow of data, and to provide uniform models for managing data that promote adaptability, yet pay heed to the physical limitations of the embedded and space environments.

  17. Adaptive Control of the Chaotic System via Singular System Approach

    Directory of Open Access Journals (Sweden)

    Yudong Li

    2014-01-01

    Full Text Available This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.

  18. Adaptive Restoration of Airborne Daedalus AADS1268 ATM Thermal Data

    International Nuclear Information System (INIS)

    D. Yuan; E. Doak; P. Guss; A. Will

    2002-01-01

    To incorporate the georegistration and restoration processes into airborne data processing in support of U.S. Department of Energy's nuclear emergency response task, we developed an adaptive restoration filter for airborne Daedalus AADS1268 ATM thermal data based on the Wiener filtering theory. Preliminary assessment shows that this filter enhances the detectability of small weak thermal anomalies in AADS1268 thermal images

  19. Contrarian behavior in a complex adaptive system

    Science.gov (United States)

    Liang, Y.; An, K. N.; Yang, G.; Huang, J. P.

    2013-01-01

    Contrarian behavior is a kind of self-organization in complex adaptive systems (CASs). Here we report the existence of a transition point in a model resource-allocation CAS with contrarian behavior by using human experiments, computer simulations, and theoretical analysis. The resource ratio and system predictability serve as the tuning parameter and order parameter, respectively. The transition point helps to reveal the positive or negative role of contrarian behavior. This finding is in contrast to the common belief that contrarian behavior always has a positive role in resource allocation, say, stabilizing resource allocation by shrinking the redundancy or the lack of resources. It is further shown that resource allocation can be optimized at the transition point by adding an appropriate size of contrarians. This work is also expected to be of value to some other fields ranging from management and social science to ecology and evolution.

  20. Atomic switch networks as complex adaptive systems

    Science.gov (United States)

    Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

    2018-03-01

    Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

  1. Robust adaptive optics systems for vision science

    Science.gov (United States)

    Burns, S. A.; de Castro, A.; Sawides, L.; Luo, T.; Sapoznik, K.

    2018-02-01

    Adaptive Optics (AO) is of growing importance for understanding the impact of retinal and systemic diseases on the retina. While AO retinal imaging in healthy eyes is now routine, AO imaging in older eyes and eyes with optical changes to the anterior eye can be difficult and requires a control and an imaging system that is resilient when there is scattering and occlusion from the cornea and lens, as well as in the presence of irregular and small pupils. Our AO retinal imaging system combines evaluation of local image quality of the pupil, with spatially programmable detection. The wavefront control system uses a woofer tweeter approach, combining an electromagnetic mirror and a MEMS mirror and a single Shack Hartmann sensor. The SH sensor samples an 8 mm exit pupil and the subject is aligned to a region within this larger system pupil using a chin and forehead rest. A spot quality metric is calculated in real time for each lenslet. Individual lenslets that do not meet the quality metric are eliminated from the processing. Mirror shapes are smoothed outside the region of wavefront control when pupils are small. The system allows imaging even with smaller irregular pupils, however because the depth of field increases under these conditions, sectioning performance decreases. A retinal conjugate micromirror array selectively directs mid-range scatter to additional detectors. This improves detection of retinal capillaries even when the confocal image has poorer image quality that includes both photoreceptors and blood vessels.

  2. CMAC-based adaptive backstepping synchronization of uncertain chaotic systems

    International Nuclear Information System (INIS)

    Lin, C.-M.; Peng, Y.-F.; Lin, M.-H.

    2009-01-01

    This study proposes an adaptive backstepping control system for synchronizing uncertain chaotic system by using cerebellar model articulation controller (CMAC). CMAC is a nonlinear network with simple computation, good generalization capability and fast learning property. The proposed CMAC-based adaptive backstepping control (CABC) system uses backstepping method and adaptive cerebellar model articulation controller (ACMAC) for synchronizing uncertain chaotic system. Finally, simulation results for the Genesio system are presented to illustrate the effectiveness of the proposed control system.

  3. Versatile multicomputer data system

    International Nuclear Information System (INIS)

    Overman, R.F.; Sand, R.J.

    1981-01-01

    A multicomputer system was designed and built to provide a means of transferring data from analytical instruments to a PDP-15 (Digital Equipment Corp., Maynard, MA) minicomputer. A model 6800 microcomputer (Motorola, Inc., Phoenix, AZ) was designed to accept data from instruments with diverse data formats and data collection times on a time-sharing basis. Once in the computer memory, the data are sent via a modified serial communications port to a PDP-15 minicomputer. The analytical instruments include an infrared spectrometer, two pulse height analyzers, an atomic absorption spectrophotometer, and a desk-top computer. This paper describes the versatility of the system, the microcomputer handling of the instrument I/O requirements, the changes in the PDP-15 to accept data at a 2400 baud rate, and changes in the TTY handler in the monitor to accommodate binary data and nonstandard byte configurations

  4. Intrusion Detection Algorithm for Mitigating Sinkhole Attack on LEACH Protocol in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ranjeeth Kumar Sundararajan

    2015-01-01

    Full Text Available In wireless sensor network (WSN, the sensors are deployed and placed uniformly to transmit the sensed data to a centralized station periodically. So, the major threat of the WSN network layer is sinkhole attack and it is still being a challenging issue on the sensor networks, where the malicious node attracts the packets from the other normal sensor nodes and drops the packets. Thus, this paper proposes an Intrusion Detection System (IDS mechanism to detect the intruder in the network which uses Low Energy Adaptive Clustering Hierarchy (LEACH protocol for its routing operation. In the proposed algorithm, the detection metrics, such as number of packets transmitted and received, are used to compute the intrusion ratio (IR by the IDS agent. The computed numeric or nonnumeric value represents the normal or malicious activity. As and when the sinkhole attack is captured, the IDS agent alerts the network to stop the data transmission. Thus, it can be a resilient to the vulnerable attack of sinkhole. Above all, the simulation result is shown for the proposed algorithm which is proven to be efficient compared with the existing work, namely, MS-LEACH, in terms of minimum computational complexity and low energy consumption. Moreover, the algorithm was numerically analyzed using TETCOS NETSIM.

  5. The state of the art in intrusion prevention and detection

    CERN Document Server

    Pathan, Al-Sakib Khan

    2013-01-01

    The State of the Art in Intrusion Prevention and Detection analyzes the latest trends and issues surrounding intrusion detection systems in computer networks, especially in communications networks. Its broad scope of coverage includes wired, wireless, and mobile networks; next-generation converged networks; and intrusion in social networks.Presenting cutting-edge research, the book presents novel schemes for intrusion detection and prevention. It discusses tracing back mobile attackers, secure routing with intrusion prevention, anomaly detection, and AI-based techniques. It also includes infor

  6. Telemetry System Data Latency

    Science.gov (United States)

    2017-07-13

    Two of the scenarios utilized the Windows Operating System on the GSSrs to broadcast the Chapter 10 data with different settings for buffer sizes...412TW-PA-17485 Telemetry System Data Latency. Jon Morgan AIR FORCE TEST CENTER EDWARDS AFB, CA 13 July 2017 4...Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202

  7. Computer Intrusions and Attacks.

    Science.gov (United States)

    Falk, Howard

    1999-01-01

    Examines some frequently encountered unsolicited computer intrusions, including computer viruses, worms, Java applications, trojan horses or vandals, e-mail spamming, hoaxes, and cookies. Also discusses virus-protection software, both for networks and for individual users. (LRW)

  8. Meta-Adaptation Strategies for Adaptation in Cyber-Physical Systems

    OpenAIRE

    Huječek, Adam

    2016-01-01

    When designing a complex Cyber-Physical System it is often impossible to foresee all potential situations in advance and prepare corresponding tactics to adapt to the changes in dynamic environment. This greatly hurts the system's resilience and dependability. All kinds of trouble can rise from situations that lie beyond the expected "envelope of adaptability" from malfunction of one component to failure of the whole system. Self-adaptation approaches are typically limited in choosing a tacti...

  9. An Adaptive Machine Vision System for Parts Assembly Inspection

    Science.gov (United States)

    Sun, Jun; Sun, Qiao; Surgenor, Brian

    This paper presents an intelligent visual inspection methodology that addresses the need for an improved adaptability of a visual inspection system for parts verification in assembly lines. The proposed system is able to adapt to changing inspection tasks and environmental conditions through an efficient online learning process without excessive off-line retraining or retuning. The system consists of three major modules: region localization, defect detection, and online learning. An edge-based geometric pattern-matching technique is used to locate the region of verification that contains the subject of inspection within the acquired image. Principal component analysis technique is employed to implement the online learning and defect detection modules. Case studies using field data from a fasteners assembly line are conducted to validate the proposed methodology.

  10. Data-acquisition systems

    International Nuclear Information System (INIS)

    Cyborski, D.R.; Teh, K.M.

    1995-01-01

    Up to now, DAPHNE, the data-acquisition system developed for ATLAS, was used routinely for experiments at ATLAS and the Dynamitron. More recently, the Division implemented 2 MSU/DAPHNE systems. The MSU/DAPHNE system is a hybrid data-acquisition system which combines the front-end of the Michigan State University (MSU) DA system with the traditional DAPHNE back-end. The MSU front-end is based on commercially available modules. This alleviates the problems encountered with the DAPHNE front-end which is based on custom designed electronics. The first MSU system was obtained for the APEX experiment and was used there successfully. A second MSU front-end, purchased as a backup for the APEX experiment, was installed as a fully-independent second MSU/DAPHNE system with the procurement of a DEC 3000 Alpha host computer, and was used successfully for data-taking in an experiment at ATLAS. Additional hardware for a third system was bought and will be installed. With the availability of 2 MSU/DAPHNE systems in addition to the existing APEX setup, it is planned that the existing DAPHNE front-end will be decommissioned

  11. Specification and Generation of Adapters for System Integration

    NARCIS (Netherlands)

    Mooij, A.J.; Voorhoeve, M.

    2013-01-01

    Large systems-of-systems are developed by integrating several smaller systems that have been developed independently. System integration often requires adaptation mechanisms for bridging any technical incompatibilities between the systems. In order to develop adapters in a faster way, we study ways

  12. Intelligent Optical Systems Using Adaptive Optics

    Science.gov (United States)

    Clark, Natalie

    2012-01-01

    Until recently, the phrase adaptive optics generally conjured images of large deformable mirrors being integrated into telescopes to compensate for atmospheric turbulence. However, the development of smaller, cheaper devices has sparked interest for other aerospace and commercial applications. Variable focal length lenses, liquid crystal spatial light modulators, tunable filters, phase compensators, polarization compensation, and deformable mirrors are becoming increasingly useful for other imaging applications including guidance navigation and control (GNC), coronagraphs, foveated imaging, situational awareness, autonomous rendezvous and docking, non-mechanical zoom, phase diversity, and enhanced multi-spectral imaging. The active components presented here allow flexibility in the optical design, increasing performance. In addition, the intelligent optical systems presented offer advantages in size and weight and radiation tolerance.

  13. IPNS data acquisition system

    International Nuclear Information System (INIS)

    Worlton, T.G.; Crawford, R.K.; Haumann, J.R.; Daly, R.

    1983-01-01

    The IPNS Data Acquisition System (DAS) was designed to be reliable, flexible, and easy to use. It provides unique methods of acquiring Time-of-Flight neutron scattering data and allows collection, storage, display, and analysis of very large data arrays with a minimum of user input. Data can be collected from normal detectors, linear position-sensitive detectors, and/or area detectors. The data can be corrected for time-delays and can be time-focussed before being binned. Corrections to be made to the data and selection of inputs to be summed are entirely software controlled, as are the time ranges and resolutions for each detector element. Each system can be configured to collect data into millions of channels. Maximum continuous data rates are greater than 2000 counts/sec with full corrections, or 16,000 counts/sec for the simpler binning scheme used with area detectors. Live displays of the data may be made as a function of time, wavevector, wavelength, lattice spacing, or energy. In most cases the complete data analysis can be done on the DAS host computer. The IPNS DAS became operational for four neutron scattering instruments in 1981 and has since been expanded to seven instruments

  14. EMIR data factory system

    Science.gov (United States)

    Rosich Minguell, Josefina; Barreto, M.; Castro, N.; Garzón, F.; Guerra, D.; Insausti, M.; López-Martín, L.; López, P.; Molgó, J.; Patrón, J.

    2014-07-01

    EMIR (Espectrógrafo Multiobjeto Infrarrojo) is a wide-field, near-infrared, multi-object spectrograph, with image capabilities, which will be located at the Nasmyth focus of GTC (Gran Telescopio Canarias). It will allow observers to obtain many intermediate resolution spectra simultaneously, in the nIR bands Z, J, H, K. A multi-slit mask unit will be used for target acquisition. This paper shows an overview of EMIR Data Factory System which main functionality is to receive raw images from DAS (Data Acquisition system), collect FITS header keywords, store images to database and propagate images to other GCS (GTC Control System) components to produce astronomical data. This system follows the standards defined by the telescope to permit the integration of this software on the GCS. The Data Factory System needs the DAS, the Sequencer, GUI and the Monitor Manager subsystems to operate. DAS generates images and sends them to the Data Factory. Sequencer and GUI (Graphical User Interface) provide information about instrument and observing program. The Monitor Manager supplies information about telescope and instrument state.

  15. Development of an Assessment Procedure for Seawater Intrusion Mitigation

    Science.gov (United States)

    Hsi Ting, F.; Yih Chi, T.

    2017-12-01

    The Pingtung Plain is one of the areas with extremely plentiful groundwater resources in Taiwan. Due to that the application of the water resource is restricted by significant variation of precipitation between wet and dry seasons, groundwater must be used as a recharge source to implement the insufficient surface water resource during dry seasons. In recent years, the coastal aquaculture rises, and the over withdrawn of groundwater by private well results in fast drop of groundwater level. Then it causes imbalance of groundwater supply and leads to serious seawater intrusion in the coastal areas. The purpose of this study is to develop an integrated numerical model of groundwater resources and seawater intrusion. Soil and Water Assessment Tool (SWAT), MODFLOW and MT3D models were applied to analyze the variation of the groundwater levels and salinity concentration to investigate the correlation of parameters, which are used to the model applications in order to disposal saltwater intrusion. The data of groundwater levels, pumping capacity and hydrogeological data to were collected to build an integrated numerical model. Firstly, we will collect the information of layered aquifer and the data of hydrological parameters to build the groundwater numerical model at Pingtung Plain, and identify the amount of the groundwater which flow into the sea. In order to deal with the future climate change conditions or extreme weather conditions, we will consider the recharge with groundwater model to improve the seawater intrusion problem. The integrated numerical model which describes that seawater intrusion to deep confined aquifers and shallow unsaturated aquifers. Secondly, we will use the above model to investigate the weights influenced by different factors to the amount area of seawater intrusion, and predict the salinity concentration distribution of evaluation at coastal area of Pingtung Plain. Finally, we will simulate groundwater recharge/ injection at the coastal

  16. Data Acquisition System

    International Nuclear Information System (INIS)

    Cirstea, C.D.; Buda, S.I.; Constantin, F.

    2005-01-01

    This paper deals with a multi parametric acquisition system developed for a four input Analog to Digital Converter working in CAMAC Standard. The acquisition software is built in MS Visual C++ on a standard PC with a USB interface. It has a visual interface which permits Start/Stop of the acquisition, setting the type of acquisition (True/Live time), the time and various menus for primary data acquisition. The spectrum is dynamically visualized with a moving cursor indicating the content and position. The microcontroller PIC16C765 is used for data transfer from ADC to PC; The microcontroller and the software create an embedded system which emulates the CAMAC protocol programming the 4 input ADC for operating modes ('zero suppression', 'addressed' and 'sequential') and handling the data transfers from ADC to its internal memory. From its memory the data is transferred into the PC by the USB interface. The work is in progress. (authors)

  17. Data acquisition system

    International Nuclear Information System (INIS)

    Cirstea, D.C.; Buda, S.I.; Constantin, F.

    2005-01-01

    The topic of this paper deals with a multi parametric acquisition system developed around a four input Analog to Digital Converter working in CAMAC Standard. The acquisition software is built in MS Visual C++ on a standard PC with a USB interface. It has a visual interface which permits Start/Stop of the acquisition, setting the type of acquisition (True/Live time), the time and various menus for primary data acquisition. The spectrum is dynamically visualized with a moving cursor indicating the content and position. The microcontroller PIC16C765 is used for data transfer from ADC to PC; The microcontroller and the software create an embedded system which emulates the CAMAC protocol programming, the 4 input ADC for operating modes ('zero suppression', 'addressed' and 'sequential') and handling the data transfers from ADC to its internal memory. From its memory the data is transferred into the PC by the USB interface. The work is in progress. (authors)

  18. Adaptive Systems in Education: A Review and Conceptual Unification

    Science.gov (United States)

    Wilson, Chunyu; Scott, Bernard

    2017-01-01

    Purpose: The purpose of this paper is to review the use of adaptive systems in education. It is intended to be a useful introduction for the non-specialist reader. Design/methodology/approach: A distinction is made between intelligent tutoring systems (ITSs) and adaptive hypermedia systems (AHSs). The two kinds of system are defined, compared and…

  19. Autonomous Rule Creation for Intrusion Detection

    Energy Technology Data Exchange (ETDEWEB)

    Todd Vollmer; Jim Alves-Foss; Milos Manic

    2011-04-01

    Many computational intelligence techniques for anomaly based network intrusion detection can be found in literature. Translating a newly discovered intrusion recognition criteria into a distributable rule can be a human intensive effort. This paper explores a multi-modal genetic algorithm solution for autonomous rule creation. This algorithm focuses on the process of creating rules once an intrusion has been identified, rather than the evolution of rules to provide a solution for intrusion detection. The algorithm was demonstrated on anomalous ICMP network packets (input) and Snort rules (output of the algorithm). Output rules were sorted according to a fitness value and any duplicates were removed. The experimental results on ten test cases demonstrated a 100 percent rule alert rate. Out of 33,804 test packets 3 produced false positives. Each test case produced a minimum of three rule variations that could be used as candidates for a production system.

  20. Data Acquisition System

    International Nuclear Information System (INIS)

    Watwood, D.; Beatty, J.

    1991-01-01

    The Data Acquisition System (DAS) is comprised of a Hewlett-Packard (HP) model 9816, Series 200 Computer System with the appropriate software to acquire, control, and archive data from a Data Acquisition/Control Unit, models HP3497A and HP3498A. The primary storage medium is an HP9153 16-megabyte hard disc. The data is backed-up on three floppy discs. One floppy disc drive is contained in the HP9153 chassis; the other two comprise an HP9122 dual disc drive. An HP82906A line printer supplies hard copy backup. A block diagram of the hardware setup is shown. The HP3497A/3498A Data Acquisition/Control Units read each input channel and transmit the raw voltage reading to the HP9816 CPU via the HPIB bus. The HP9816 converts this voltage to the appropriate engineering units using the calibration curves for the sensor being read. The HP9816 archives both the raw and processed data along with the time and the readings were taken to hard and floppy discs. The processed values and reading time are printed on the line printer. This system is designed to accommodate several types of sensors; each type is discussed in the following sections