WorldWideScience

Sample records for adaptive intrusion data systems

  1. Adaptive Intrusion Data System (AIDS)

    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

  2. Adaptive intrusion data system (AIDS) software routines

    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

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

    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

  4. Memory controlled data processor. [Data collector and formatter for adaptive Intrusion Data System

    Johnson, C.S.

    1977-12-01

    The Memory Controlled Data Processor (MCDP) was designed to provide a high-speed multichannel processor and data formater for the Adaptive Intrusion Data System. It can address up to 48 analog data channels, 48 bilevel alarm data channels, and numerous miscellaneous data channels such as weather and time. A digital comparator in the MCDP can make comparisons between the data being processed and threshold limits programed for any channel. The MCDP is software oriented and has its instructions stored in a 4K core memory. 8 figures, 7 tables.

  5. An Adaptive Database Intrusion Detection System

    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…

  6. Data Mining and Intrusion Detection Systems

    Zibusiso Dewa; Leandros A. Maglaras

    2016-01-01

    The rapid evolution of technology and the increased connectivity among its components, imposes new cyber-security challenges. To tackle this growing trend in computer attacks and respond threats, industry professionals and academics are joining forces in order to build Intrusion Detection Systems (IDS) that combine high accuracy with low complexity and time efficiency. The present article gives an overview of existing Intrusion Detection Systems (IDS) along with their main principles. Also th...

  7. Adaptive critic design for computer intrusion detection system

    Novokhodko, Alexander; Wunsch, Donald C., II; Dagli, Cihan H.

    2001-03-01

    This paper summarizes ongoing research. A neural network is used to detect a computer system intrusion basing on data from the system audit trail generated by Solaris Basic Security Module. The data have been provided by Lincoln Labs, MIT. The system alerts the human operator, when it encounters suspicious activity logged in the audit trail. To reduce the false alarm rate and accommodate the temporal indefiniteness of moment of attack a reinforcement learning approach is chosen to train the network.

  8. An Adaptive Hybrid Multi-level Intelligent Intrusion Detection System for Network Security

    P. Ananthi

    2014-04-01

    Full Text Available Intrusion Detection System (IDS plays a vital factor in providing security to the networks through detecting malicious activities. Due to the extensive advancements in the computer networking, IDS has become an active area of research to determine various types of attacks in the networks. A large number of intrusion detection approaches are available in the literature using several traditional statistical and data mining approaches. Data mining techniques in IDS observed to provide significant results. Data mining approaches for misuse and anomaly-based intrusion detection generally include supervised, unsupervised and outlier approaches. It is important that the efficiency and potential of IDS be updated based on the criteria of new attacks. This study proposes a novel Adaptive Hybrid Multi-level Intelligent IDS (AHMIIDS system which is the combined version of anomaly and misuse detection techniques. The anomaly detection is based on Bayesian Networks and then the misuse detection is performed using Adaptive Neuro Fuzzy Inference System (ANFIS. The outputs of both anomaly detection and misuse detection modules are applied to Decision Table Majority (DTM to perform the final decision making. A rule-base approach is used in this system. It is observed from the results that the proposed AHMIIDS performs better than other conventional hybrid IDS.

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

    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.

  10. Intrusion Prevention in Depth System Research Based on Data Mining

    Wang Jie; Zheng Xiao; Liu Yabin; Shi Chenghui

    2009-01-01

    This article proposes a data mining based intrusion prevention in depth system model to manage the huge amounts of unreliable and uncontrollable security events, which are generated by the extensive utilization of heterogeneous security devices in computer networks. A method of combining online detection and offline data mining is made use of as the core of the model. On the other hand, the work process of the system can be compartmentalized into two phases: online examination through pattern...

  11. The Design and Implementation of Intrusion Detection System based on Data Mining Technology

    Qinglei Zhou; Yilin Zhao

    2013-01-01

    Intrusion detection technology is a research hotspot in the field of information security. This study introduces the types of traditional intrusion detection and data mining technology; Aiming at the defects and limitations of current intrusion detection system, the study has fused the data mining technology into intrusion detection model, and has designed and implemented the intrusion detection system based on data mining technology with the preliminary research and exploration.

  12. Using Adaptive Neuro-Fuzzy Inference System in Alert Management of Intrusion Detection Systems

    Zahra Atashbar Orang

    2012-10-01

    Full Text Available By ever increase in using computer network and internet, using Intrusion Detection Systems (IDS has been more important. Main problems of IDS are the number of generated alerts, alert failure as well as identifying the attack type of alerts. In this paper a system is proposed that uses Adaptive Neuro-Fuzzy Inference System to classify IDS alerts reducing false positive alerts and also identifying attack types of true positive ones. By the experimental results on DARPA KDD cup 98, the system can classify alerts, leading a reduction of false positive alerts considerably and identifying attack types of alerts in low slice of time.

  13. Adapting safety requirements analysis to intrusion detection

    Lutz, R.

    2001-01-01

    Several requirements analysis techniques widely used in safety-critical systems are being adapted to support the analysis of secure systems. Perhaps the most relevant system safety techique for Intrusion Detection Systems is hazard analysis.

  14. Interior intrusion detection systems

    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.

  15. Interior intrusion detection systems

    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

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

    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

  17. MA- IDS: A Distributed Intrusion Detection System Based on Data Mining

    SUN Jian-hua; JIN Hai; CHEN Hao; HAN Zong-fen

    2005-01-01

    Aiming at the shortcomings in intrusion detection systems (IDSs) used in commercial and research fields,we propose the MA-IDS system, a distributed intrusion detection system based on data mining. In this model, misuse intrusion detection system (MIDS) and anomaly intrusion detection system (AIDS) are combined. Data mining is applied to raise detection performance, and distributed mechanism is employed to increase the scalability and efficiency. Host- and network-based mining algorithms employ an improved Bayesian decision theorem that suits for real security environment to minimize the risks incurred by false decisions. We describe the overall architecture of the MA-IDS system, and discuss specific design and implementation issue.

  18. A Survey and Comparative Analysis of Data Mining Techniques for Network Intrusion Detection Systems

    Reema Patel; Amit Thakkar; Amit Ganatra

    2012-01-01

    Despite of growing information technology widely, security has remained one challenging area for computers and networks. In information security, intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or availability of a resource. Currently many researchers have focused on intrusion detection system based on data mining techniques as an efficient artifice. Data mining is one of the technologies applied to intrusion detection to invent a ...

  19. Combining Naive Bayes and Decision Tree for Adaptive Intrusion Detection

    Farid, Dewan Md; Rahman, Mohammad Zahidur; 10.5121/ijnsa.2010.2202

    2010-01-01

    In this paper, a new learning algorithm for adaptive network intrusion detection using naive Bayesian classifier and decision tree is presented, which performs balance detections and keeps false positives at acceptable level for different types of network attacks, and eliminates redundant attributes as well as contradictory examples from training data that make the detection model complex. The proposed algorithm also addresses some difficulties of data mining such as handling continuous attribute, dealing with missing attribute values, and reducing noise in training data. Due to the large volumes of security audit data as well as the complex and dynamic properties of intrusion behaviours, several data miningbased intrusion detection techniques have been applied to network-based traffic data and host-based data in the last decades. However, there remain various issues needed to be examined towards current intrusion detection systems (IDS). We tested the performance of our proposed algorithm with existing learn...

  20. Intrusion Detection Systems

    Pietro, Roberto Di

    2008-01-01

    In our world of ever-increasing Internet connectivity, there is an on-going threat of intrusion, denial of service attacks, or countless other abuses of computer and network resources. In particular, these threats continue to persist due to the flaws of current commercial intrusion detection systems (IDSs). Intrusion Detection Systems is an edited volume by world class leaders in this field. This edited volume sheds new light on defense alert systems against computer and network intrusions. It also covers integrating intrusion alerts within security policy framework for intrusion response, rel

  1. Adaptive Genetic Algorithm Model for Intrusion Detection

    K. S. Anil Kumar

    2012-09-01

    Full Text Available Intrusion detection systems are intelligent systems designed to identify and prevent the misuse of computer networks and systems. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Thus the emerging network security systems need be part of the life system and this ispossible only by embedding knowledge into the network. The Adaptive Genetic Algorithm Model - IDS comprising of K-Means clustering Algorithm, Genetic Algorithm and Neural Network techniques. Thetechnique is tested using multitude of background knowledge sets in DARPA network traffic datasets.

  2. Combining Naive Bayes and Decision Tree for Adaptive Intrusion Detection

    Dewan Md. Farid

    2010-04-01

    Full Text Available In this paper, a new learning algorithm for adaptive network intrusion detection using naive Bayesian classifier and decision tree is presented, which performs balance detections and keeps false positives at acceptable level for different types of network attacks, and eliminates redundant attributes as well as contradictory examples from training data that make the detection model complex. The proposedalgorithm also addresses some difficulties of data mining such as handling continuous attribute, dealing with missing attribute values, and reducing noise in training data. Due to the large volumes of security audit data as well as the complex and dynamic properties of intrusion behaviours, several data miningbased intrusion detection techniques have been applied to network-based traffic data and host-based data in the last decades. However, there remain various issues needed to be examined towards current intrusion detection systems (IDS. We tested the performance of our proposed algorithm with existing learning algorithms by employing on the KDD99 benchmark intrusion detection dataset. The experimental results prove that the proposed algorithm achieved high detection rates (DR andsignificant reduce false positives (FP for different types of network intrusions using limited computational resources

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

    VANCEA, F.

    2014-01-01

    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 discre...

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

    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.

  5. WLAN Intrusion Detection System

    Ms. Sushama Shirke

    2011-08-01

    Full Text Available This is an implementation of the Wireless LAN Intrusion Detection System (WIDS using clock-skews as a fingerprinting property as suggested by Jana-Kasera [1]. Our objective is to detect the presence of a fake access point (AP in a Wireless LAN (WLAN. Use of clock -skew enables us to effectively detect Medium Access Control (MAC Address spoofing. The principle used in this project is that clock s k e w s remain consistent over time for the same AP but vary significantly across AP’s. We have also tried to exploreprobable points of failure and implemented algorithms to overcome these problems. Advantage of this implementation is that fake AP can be detected very quickly as WLAN Intrusion Detection System needs only 100 -200 packets in most cases.

  6. Wireless Intrusion Prevention Systems

    Jack TIMOFTE

    2008-01-01

    The wireless networks have changed the way organizations work and offered a new range of possibilities, but at the same time they introduced new security threats. While an attacker needs physical access to a wired network in order to launch an attack, a wireless network allows anyone within its range to passively monitor the traffic or even start an attack. One of the countermeasures can be the use of Wireless Intrusion Prevention Systems.

  7. A Comprehensive Study in Data Mining Frameworks for Intrusion Detection

    R.Venkatesan, R. Ganesan, A. Arul Lawrence Selvakumar

    2012-01-01

    Intrusions are the activities that violate the security policy of system. Intrusion Detection is the process used to identify intrusions. Network security is to be considered as a major issue in recent years, since the computer network keeps on expanding every day. An Intrusion Detection System (IDS) is a system for detecting intrusions and reporting to the authority or to the network administration. Data mining techniques have been successfully applied in many fields like Network Management,...

  8. Experiments on Adaptive Techniques for Host-Based Intrusion Detection

    This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerable preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment

  9. Adaptable data management for systems biology investigations

    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.

  10. WLAN Intrusion Detection System

    Ms. Sushama Shirke; Mr. S.B.Vanjale

    2011-01-01

    This is an implementation of the Wireless LAN Intrusion Detection System (WIDS ) using clock-skews as a fingerprinting property as suggested by Jana-Kasera [1]. Our objective is to detect the presence of a fake access point (AP) in a Wireless LAN (WLAN). Use of clock -skew enables us to effectively detect Medium Access Control (MAC) Address spoofing. The principle used in this project is that clock s k e w s remain consistent over time for the same AP but vary significantly across AP’s. We ha...

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

    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.

  12. Rapid deployment intrusion detection system

    A rapidly deployable security system is one that provides intrusion detection, assessment, communications, and annunciation capabilities; is easy to install and configure; can be rapidly deployed, and is reusable. A rapidly deployable intrusion detection system (RADIDS) has many potential applications within the DOE Complex: back-up protection for failed zones in a perimeter intrusion detection and assessment system, intrusion detection and assessment capabilities in temporary locations, protection of assets during Complex reconfiguration, and protection in hazardous locations, protection of assets during Complex reconfiguration, and protection in hazardous locations. Many DOE user-need documents have indicated an interest in a rapidly deployable intrusion detection system. The purpose of the RADIDS project is to design, develop, and implement such a system. 2 figs

  13. Data Visualization Technique Framework for Intrusion detection

    Alaa El - Din Riad; Ibrahim Elhenawy; Ahmed Hassan; Nancy Awadallah

    2011-01-01

    Network attacks have become the fundamental threat to today's largely interconnected computer system. Intrusion detection system (IDS) is indispensable to defend the system in the face of increasing vulnerabilities. While a number of information visualization software frameworks exist, creating new visualizations, especially those that involve novel visualization metaphors, interaction techniques, data analysis strategies, and specialized rendering algorithms, is still often a difficult proce...

  14. Introduction to Wireless Intrusion Detection Systems

    Milliken, Jonny

    2014-01-01

    The IDS (Intrusion Detection System) is a common means of protecting networked systems from attack or malicious misuse. The development and rollout of an IDS can take many different forms in terms of equipment, protocols, connectivity, cost and automation. This is particularly true of WIDS (Wireless Intrusion Detection Systems) which have many more opportunities and challenges associated with data transmission through an open, shared medium. The operation of a WIDS is a multistep process from...

  15. A Comprehensive Study in Data Mining Frameworks for Intrusion Detection

    R.Venkatesan, R. Ganesan, A. Arul Lawrence Selvakumar

    2012-12-01

    Full Text Available Intrusions are the activities that violate the security policy of system. Intrusion Detection is the process used to identify intrusions. Network security is to be considered as a major issue in recent years, since the computer network keeps on expanding every day. An Intrusion Detection System (IDS is a system for detecting intrusions and reporting to the authority or to the network administration. Data mining techniques have been successfully applied in many fields like Network Management, Education, Science, Business, Manufacturing, Process control, and Fraud Detection. Data Mining for IDS is the technique which can be used mainly to identify unknown attacks and to raise alarms when security violations are detected. The purpose of this survey paper is to describe the methods/ techniques which are being used for Intrusion Detection based on Data mining concepts and the designed frame works for the same. We are also going to review the related works for intrusion detection.

  16. Intrusion Detection By Data Mining Algorithms: A Review

    Rafsanjani, Marjan Kuchaki; Varzaneha, Zahra Asghari

    2013-01-01

    – With the increasing use of network-based services and sensitive information on networks, maintaining information security is essential. Intrusion Detection System is a security tool used to detect unauthorized activities of a computer system or network. Data mining is one of the technologies applied to intrusion detection. This article introduces various data mining techniques used to implement an intrusion detection system. Then reviews some of the related studies focusing on data mining a...

  17. Network Intrusion Forensic Analysis Using Intrusion Detection System

    Manish Kumar

    2011-05-01

    Full Text Available The need for computer intrusion forensics arises from the alarming increase in the number of computer crimes that are committed annually. After a computer system has been breached and an intrusion has been detected, there is a need for a computer forensics investigation to follow. Computer forensics is used to bring to justice, those responsible for conducting attacks on computer systems throughout the world. Because of this the law must be follow precisely when conducting a forensics investigation. It is not enough to simple know an attacker is responsible for the crime, the forensics investigation must be carried out in a precise manner that will produce evidence that is amicable in a court room. For computer intrusion forensics many methodologies have been designed to be used when conducting an investigation. With the birth of the Internet and networks, the computer intrusion has never been as significant as it is now. There are different preventive measures available, such as access control and authentication, to attempt to prevent intruders. Intrusion detection systems (IDS are developed to detect an intrusion as it occurs, and to execute countermeasures when detected. Intrusion detection (ID takes over where preventive security fails. In order to choose the best IDS for a given system, one should be aware of the advantages and disadvantages of the each IDS. This paper views a forensic application within the framework of Intrusion Detection and details the advantages and disadvantages of IDS.

  18. Building Intrusion Tolerant Software System

    PENG Wen-ling; WANG Li-na; ZHANG Huan-guo; CHEN Wei

    2005-01-01

    In this paper, we describe and analyze the hypothesis about intrusion tolerance software system, so that it can provide an intended server capability and deal with the impacts caused by the intruder exploiting the inherent security vulnerabilities. We present some intrusion tolerance technology by exploiting N-version module threshold method in constructing multilevel secure software architecture, by detecting with hash value, by placing an "antigen" word next to the return address on the stack that is similar to human immune system, and by adding "Honey code" nonfunctional code to disturb intruder, so that the security and the availability of the software system are ensured.

  19. Enhanced Intrusion Detection System for Malicious Node Detection in Mobile Ad hoc Networks using Data Transmission Quality of Nodes

    S. Mamatha

    2014-09-01

    Full Text Available Mobile Ad hoc NETworks (MANETs are the new generation of networks that offer unrestricted mobility without any underlying infrastructure. It relies on the cooperation of all the participating nodes. Due to their open nature and lack of infrastructure, security for MANETS has become an intricate problem than the security in other networks. The conventional security mechanisms of protecting a wired network are not sufficient for these networks. Hence a second level of defense to detect and respond to the security problem called an Intrusion detection system is required. Generally the malicious nodes demonstrate a different behavioral pattern of all the other normal nodes. So an Intrusion Detection System based on anomaly based intrusion detection that works by checking the behavior of the nodes was proposed. Here, in this paper to determine the behavior of the nodes as malicious or legitimate a Data Transmission Quality (DTQ function is used. The DTQ function is defined in such a way that it will be close to a constant or keep changing smoothly for genuine nodes and will keep on diminishing for malicious nodes.. The final decision of confirming nodes as malicious is determined by a group consensus method. The evaluation results show that the proposed method increases the detection rate as well as decreases the false positive rate.

  20. A Microcontroller Based Intrusion Detection System

    Ewunonu Toochi

    2014-11-01

    Full Text Available A Microcontroller based Intrusion Detection System is designed and implemented. Rampant, Okintrusion to restricted zones have highlighted the need for embedded systems that can effectively monitor, instantly alert personnel of any breach in security and retrieve graphic evidence of any such activity in the secured area. At the heart of the intrusion detection system is the PIC 168F77A Microcontroller that transmits pulses at 38 KHz. It is suitably interfaced to a GSM modem that can send SMS on sight of infringement and a webcam that can take snapshots. The report also presents the system software which has been developed in two parts: one in C++ Language using MPLAB KIT and the other written in AT COMMAND resident in the GSM modem. The system is very cost-effective, uses easily available components and is adaptable to control systems.

  1. Novel Intrusion Detection using Probabilistic Neural Network and Adaptive Boosting

    Tran, Tich Phuoc; Tran, Dat; Nguyen, Cuong Duc

    2009-01-01

    This article applies Machine Learning techniques to solve Intrusion Detection problems within computer networks. Due to complex and dynamic nature of computer networks and hacking techniques, detecting malicious activities remains a challenging task for security experts, that is, currently available defense systems suffer from low detection capability and high number of false alarms. To overcome such performance limitations, we propose a novel Machine Learning algorithm, namely Boosted Subspace Probabilistic Neural Network (BSPNN), which integrates an adaptive boosting technique and a semi parametric neural network to obtain good tradeoff between accuracy and generality. As the result, learning bias and generalization variance can be significantly minimized. Substantial experiments on KDD 99 intrusion benchmark indicate that our model outperforms other state of the art learning algorithms, with significantly improved detection accuracy, minimal false alarms and relatively small computational complexity.

  2. Novel Intrusion Detection using Probabilistic Neural Network and Adaptive Boosting

    Tich Phuoc Tran

    2009-10-01

    Full Text Available This article applies Machine Learning techniques to solve Intrusion Detection problems withincomputer networks. Due to complex and dynamic nature of computer networks and hacking techniques, detecting malicious activities remains a challenging task for security experts, that is, currently available defense systems suffer from low detection capability and high number of false alarms. To overcome such performance limitations, we propose a novel Machine Learning algorithm, namely Boosted Subspace Probabilistic Neural Network (BSPNN, which integrates an adaptive boosting technique and a semi-parametric neural network to obtain good trade-off between accuracy and generality. As the result, learning bias and generalization variance can be significantly minimized. Substantial experiments on KDD-99 intrusion benchmark indicate that our model outperforms other state-of-the-art learning algorithms, with significantly improved detection accuracy, minimal false alarms and relatively small computational complexity.

  3. An Intrusion Detection System Framework for Ad Hoc Networks

    Arjun Singh; Surbhi Chauhan; Kamal Kant; Reshma Doknaia

    2012-01-01

    Secure and efficient communication among a set of mobile nodes is one of the most important aspects in ad-hoc wireless networks. Wireless networks are particularly vulnerable to intrusion, as they operate in open medium, and use cooperative strategies for network communications. By efficiently merging audit data from multiple network sensors, we analyze the entire ad hoc wireless network for intrusions and try to inhibit intrusion attempts. This paper presents an intrusion detection system fo...

  4. WiFi Miner: An Online Apriori-Infrequent Based Wireless Intrusion System

    Rahman, Ahmedur; Ezeife, C. I.; Aggarwal, A. K.

    Intrusion detection in wireless networks has become a vital part in wireless network security systems with wide spread use of Wireless Local Area Networks (WLAN). Currently, almost all devices are Wi-Fi (Wireless Fidelity) capable and can access WLAN. This paper proposes an Intrusion Detection System, WiFi Miner, which applies an infrequent pattern association rule mining Apriori technique to wireless network packets captured through hardware sensors for purposes of real time detection of intrusive or anomalous packets. Contributions of the proposed system includes effectively adapting an efficient data mining association rule technique to important problem of intrusion detection in a wireless network environment using hardware sensors, providing a solution that eliminates the need for hard-to-obtain training data in this environment, providing increased intrusion detection rate and reduction of false alarms.

  5. Research on IPv6 intrusion detection system Snort-based

    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.

  6. Coupling of hydrogeological models with hydrogeophysical data to characterize seawater intrusion and shallow geothermal systems

    Beaujean, J.; Kemna, A.; Engesgaard, P. K.; Hermans, T.; Vandenbohede, A.; Nguyen, F.

    2013-12-01

    While coastal aquifers are being stressed due to climate changes and excessive groundwater withdrawals require characterizing efficiently seawater intrusion (SWI) dynamics, production of geothermal energy is increasingly being used to hinder global warming. To study these issues, we need both robust measuring technologies and reliable predictions based on numerical models. SWI models are currently calibrated using borehole observations. Similarly, geothermal models depend mainly on the temperature field at few locations. Electrical resistivity tomography (ERT) can be used to improve these models given its high sensitivity to TDS and temperature and its relatively high lateral resolution. Inherent geophysical limitations, such as the resolution loss, can affect the overall quality of the ERT images and also prevent the correct recovery of the desired hydrochemical property. We present an uncoupled and coupled hydrogeophysical inversion to calibrate SWI and thermohydrogeologic models using ERT. In the SWI models, we demonstrate with two synthetic benchmarks (homogeneous and heterogeneous coastal aquifers) the ability of cumulative sensitivity-filtered ERT images using surface-only data to recover the hydraulic conductivity. Filtering of ERT-derived data at depth, where resolution is poorer, and the model errors make the dispersivity more difficult to estimate. In the coupled approach, we showed that parameter estimation is significantly improved because regularization bias is replaced by forward modeling only. Our efforts are currently focusing on applying the uncoupled/coupled approaches on a real life case study using field data from the site of Almeria, SE Spain. In the thermohydrogeologic models, the most sensitive hydrologic parameters responsible for heat transport are estimated from surface ERT-derived temperatures and ERT resistance data. A real life geothermal experiment that took place on the Campus De Sterre of Ghent University, Belgium and a synthetic

  7. Multi-Vector Portable Intrusion Detection System

    Moyers, Benjamin

    2009-01-01

    This research describes an intrusion detection system designed to fulfill the need for increased mobile device security. The Battery-Sensing Intrusion Protection System (B-SIPS) [1] initially took a non-conventional approach to intrusion detection by recognizing attacks based on anomalous Instantaneous Current (IC) drainage. An extension of B-SIPS, the Multi-Vector Portable Intrusion Detection System (MVP-IDS) validates the idea of recognizing attacks based on anomalous IC drain by correlat...

  8. Evaluation of Intrusion Detection Systems

    Ulvila, Jacob W.; Gaffney, John E.

    2003-01-01

    This paper presents a comprehensive method for evaluating intrusion detection systems (IDSs). It integrates and extends ROC (receiver operating characteristic) and cost analysis methods to provide an expected cost metric. Results are given for determining the optimal operation of an IDS based on this expected cost metric. Results are given for the operation of a single IDS and for a combination of two IDSs. The method is illustrated for: 1) determining the best operating point for a single an...

  9. Intrusion Detection System: Security Monitoring System

    ShabnamNoorani,; Sharmila Gaikwad Rathod

    2015-01-01

    An intrusion detection system (IDS) is an ad hoc security solution to protect flawed computer systems. It works like a burglar alarm that goes off if someone tampers with or manages to get past other security mechanisms such as authentication mechanisms and firewalls. An Intrusion Detection System (IDS) is a device or a software application that monitors network or system activities for malicious activities or policy violations and produces reports to a management station.Intrusio...

  10. Network Intrusion Detection System Based On Machine Learning Algorithms

    Vipin Das; Vijaya Pathak; Sattvik Sharma; Sreevathsan; MVVNS.Srikanth; Gireesh Kumar T

    2010-01-01

    Network and system security is of paramount importance in the present data communication environment. Hackers and intruders can create many successful attempts to cause the crash of the networks and web services by unauthorized intrusion. New threats and associated solutions to prevent these threats are emerging together with the secured system evolution. Intrusion Detection Systems (IDS) are one of these solutions. The main function of Intrusion Detection System is to protect the resources f...

  11. Averaging analysis for discrete time and sampled data adaptive systems

    Fu, Li-Chen; Bai, Er-Wei; Sastry, Shankar S.

    1986-01-01

    Earlier continuous time averaging theorems are extended to the nonlinear discrete time case. Theorems for the study of the convergence analysis of discrete time adaptive identification and control systems are used. Instability theorems are also derived and used for the study of robust stability and instability of adaptive control schemes applied to sampled data systems. As a by product, the effects of sampling on unmodeled dynamics in continuous time systems are also studied.

  12. Smart sensor systems for outdoor intrusion detection

    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. An Implementation of Intrusion Detection System Using Genetic Algorithm

    Mohammad Sazzadul Hoque; Md. Abdul Mukit; Md. Abu Naser Bikas

    2012-01-01

    Nowadays it is very important to maintain a high level security to ensure safe and trusted communication of information between various organizations. But secured data communication over internet and any other network is always under threat of intrusions and misuses. So Intrusion Detection Systems have become a needful component in terms of computer and network security. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not co...

  14. An Implementation of Intrusion Detection System Using Genetic Algorithm

    Hoque, Mohammad Sazzadul; Mukit, Md. Abdul; Bikas, Md. Abu Naser

    2012-01-01

    Nowadays it is very important to maintain a high level security to ensure safe and trusted communication of information between various organizations. But secured data communication over internet and any other network is always under threat of intrusions and misuses. So Intrusion Detection Systems have become a needful component in terms of computer and network security. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not com...

  15. A Survey on Intrusion Detection using Data Mining Techniques

    Venkatesan, R

    2012-01-01

    Intrusions are the activities that violate the security policy of system. Intrusion Detection is the process used to identify intrusions. Network security is to be considered as a major issue in recent years, since the computer network keeps on extending dramatically. Information Systems and Networks are subject to electronic attacks and the possibilities of intrusion are very high.  An Intrusion Detection System (IDS) is a system for detecting intrusions and reporting to the authority or to ...

  16. Classification and Importance of Intrusion Detection System

    Rajasekaran K

    2012-08-01

    Full Text Available An intrusion detection system (IDS is a device or software application that monitors network or system activities for malicious activities or policy violations and produces reports to a Management Station. Some systems may attempt to stop an intrusion attempt but this is neither required nor expected of a monitoring system. Due to a growing number of intrusion events and also because the Internet and local networks have become so ubiquitous, organizations are increasingly implementing various systems that monitor IT security breaches. This includes an overview of the classification of intrusion detection systems and introduces the reader to some fundamental concepts of IDS methodology: audit trail analysis and on-the-fly processing as well as anomaly detection and signature detection approaches. This research paper discusses the primary intrusion detection techniques and the classification of intrusion Detection system.

  17. Intrusion Detection System: Security Monitoring System

    ShabnamNoorani,

    2015-10-01

    Full Text Available An intrusion detection system (IDS is an ad hoc security solution to protect flawed computer systems. It works like a burglar alarm that goes off if someone tampers with or manages to get past other security mechanisms such as authentication mechanisms and firewalls. An Intrusion Detection System (IDS is a device or a software application that monitors network or system activities for malicious activities or policy violations and produces reports to a management station.Intrusion Detection System (IDS has been used as a vital instrument in defending the network from this malicious or abnormal activity..In this paper we are comparing host based and network based IDS and various types of attacks possible on IDS.

  18. Implementation of an Intrusion Detection System

    Saidi Ben Boubaker Ourida

    2012-01-01

    Securing networks and data is among interesting issues of computer science research and practice. Many approaches and techniques have been developed to secure computer architectures, they addressed several layers, e.g, physical security, applications and encryption algorithms, etc. In this paper, we address the problem of securing large networks with complex architectures, based on intrusion detection systems. Based on the experimentations performed, we demonstrated the efficiency of our solu...

  19. Performance Enhancement of Intrusion Detection using Neuro - Fuzzy Intelligent System

    Dr. K. S. Anil Kumar

    2014-10-01

    Full Text Available This research work aims at developing hybrid algorithms using data mining techniques for the effective enhancement of anomaly intrusion detection performance. Many proposed algorithms have not addressed their reliability with varying amount of malicious activity or their adaptability for real time use. The study incorporates a theoretical basis for improvement in performance of IDS using K-medoids Algorithm, Fuzzy Set Algorithm, Fuzzy Rule System and Neural Network techniques. Also statistical significance of estimates has been looked into for finalizing the best one using DARPA network traffic datasets.

  20. Testing Of Network Intrusion Detection System

    Jagadeep Vegunta

    2011-11-01

    Full Text Available Network based intrusion detection system use the models of attacks to identify intrusive behavior ability of systems to detect attacks by quality of models which are called signatures. Some attacks exploits in different ways. For this reason we use testing tools that able to detect goodness of signatures. This technique describes test and evaluate misuse detection models in the case of network-based intrusion detection systems. we use Mutant Exploits are working against vulnerability applications. This mutant exploit is based on mechanism to generate large no. of exploit by applying mutant operators. The results of the systems in detecting these variations pro-vide a quantitative basis for the evaluation of the quality of the corresponding detection model. but here we are going to find defects of this testing and is this test will provide 100% security for this system (or not. and also which technique gives much security among these techniques fuzzy logic, neural networks, hybrid fuzzy and neural networks, naïve bayes, genetic algorithms and data mining.

  1. An Implementation of Intrusion Detection System Using Genetic Algorithm

    Mohammad Sazzadul Hoque

    2012-03-01

    Full Text Available Nowadays it is very important to maintain a high level security to ensure safe and trusted communication of information between various organizations. But secured data communication over internet and any other network is always under threat of intrusions and misuses. So Intrusion Detection Systems have become a needful component in terms of computer and network security. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not completely flawless. So, the quest of betterment continues. In this progression, here we present an Intrusion Detection System (IDS, by applying genetic algorithm (GA to efficiently detect various types of network intrusions. Parameters and evolution processes for GA are discussed in details and implemented. This approach uses evolution theory to information evolution in order to filter the traffic data and thus reduce the complexity. To implement and measure the performance of our system we used the KDD99 benchmark dataset and obtained reasonable detection rate.

  2. Abstracting audit data for lightweight intrusion detection

    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.

  3. Intrusion-Tolerant Based Survivable Model of Database System

    ZHUJianming; WANGChao; MAJianfeng

    2005-01-01

    Survivability has become increasingly important with society's increased dependence of critical infrastructures on computers. Intrusiontolerant systems extend traditional secure systems to be able to survive or operate through attacks, thus it is an approach for achieving survivability. This paper proposes survivable model of database system based on intrusion-tolerant mechanisms. The model is built on three layers security architecture, to defense intrusion at the outer layer, to detect intrusion at the middle layer, and to tolerate intrusion at the inner layer. We utilize the techniques of both redundancy and diversity and threshold secret sharing schemes to implement the survivability of database and to protect confidential data from compromised servers in the presence of intrusions. Comparing with the existing schemes, our approach has realized the security and robustness for the key functions of a database system by using the integration security strategy and multiple security measures.

  4. A Survey of Intrusion Detection System in Big Data%大数据环境下入侵检测系统概述

    葛钊成; 彭凯

    2016-01-01

    入侵检测系统(Intrusion Detection System, IDS)为网络空间安全做出重大贡献。然而随着大数据时代的到来,IDS 暴露出效率低下、理念落后等系统性不足。本文结合大数据特征及传统 IDS 技术的不足,针对性地概述了分布式入侵检测系统(Districted Intrusion Detection System, DIDS),并在基本概念、系统分类和性能特点等方面对其做出重点解释。最后从深度学习、广度融合等角度展望了入侵检测技术的未来发展。%Intrusion detection system has made a great contribution for cyberspace security. However, with the approach of the age of big data, IDS has exposed certain structural defects, such as inefficiency and conservative ideas. Combining with the characteristic of big data and traditional IDS techniques, this paper provides a survey of distributed intrusion detection system (DIDS) and makes detailed explanations on concepts, classifications and performance. The paper also prospects the development of IDS from the perspective of deep learning, extensive integration, etc.

  5. DESIGN AND IMPLEMENTATION OF A REAL TIME INTRUSION DETECTION SYSTEM

    ARICI, Nursal; YILDIZ, Elmas

    2010-01-01

    Intrusion detection systems also takes place among the enhanced security policies by coming into prominence of knowledge day by day. Intrusion Detection Systems are security systems that detect attacks on computer systems and network sources, identify from whom attacks comes, recognize abnormal situtations by monitoring system and aim to take precautions against them. Detection of abnormal situations takes place in issue of data mining. DoS attacks are used to block access to a resource an...

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

    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

  7. Intrusion Detection Systems in Wireless Sensor Networks: A Review

    Nabil Ali Alrajeh; Khan, S.; Bilal Shams

    2013-01-01

    Wireless Sensor Networks (WSNs) consist of sensor nodes deployed in a manner to collect information about surrounding environment. Their distributed nature, multihop data forwarding, and open wireless medium are the factors that make WSNs highly vulnerable to security attacks at various levels. Intrusion Detection Systems (IDSs) can play an important role in detecting and preventing security attacks. This paper presents current Intrusion Detection Systems and some open research problems relat...

  8. NETWORK INTRUSION DETECTION SYSTEM USING FUZZY LOGIC

    R. Shanmugavadivu

    2011-02-01

    Full Text Available IDS which are increasingly a key part of system defense are used to identify abnormal activities in a computer system. In general, the traditional intrusion detection relies on the extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, variousdata-mining and machine learning techniques have been used in the literature. In the proposed system, we have designed fuzzy logic-based system for effectively identifying the intrusion activities within a network. The proposed fuzzy logic-based system can be able to detect an intrusion behavior of the networks since the rule base contains a better set of rules. Here, we have used automated strategy for generation of fuzzy rules, which are obtained from the definite rules using frequent items. The experiments and evaluations of the proposed intrusion detection system are performed with the KDD Cup 99 intrusion detection dataset. The experimentalresults clearly show that the proposed system achieved higher precision in identifying whether the records are normal or attack one.

  9. Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System

    Aranki, Nazeeh I.; Keymeulen, Didier; Kimesh, Matthew A.

    2012-01-01

    Modern hyperspectral imaging systems are able to acquire far more data than can be downlinked from a spacecraft. Onboard data compression helps to alleviate this problem, but requires a system capable of power efficiency and high throughput. Software solutions have limited throughput performance and are power-hungry. Dedicated hardware solutions can provide both high throughput and power efficiency, while taking the load off of the main processor. Thus a hardware compression system was developed. The implementation uses a field-programmable gate array (FPGA). The implementation is based on the fast lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral-Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which achieves excellent compression performance and has low complexity. This algorithm performs predictive compression using an adaptive filtering method, and uses adaptive Golomb coding. The implementation also packetizes the coded data. The FL algorithm is well suited for implementation in hardware. In the FPGA implementation, one sample is compressed every clock cycle, which makes for a fast and practical realtime solution for space applications. Benefits of this implementation are: 1) The underlying algorithm achieves a combination of low complexity and compression effectiveness that exceeds that of techniques currently in use. 2) The algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. 3) Hardware acceleration provides a throughput improvement of 10 to 100 times vs. the software implementation. A prototype of the compressor is available in software, but it runs at a speed that does not meet spacecraft requirements. The hardware implementation targets the Xilinx Virtex IV FPGAs, and makes the use of this compressor practical for Earth satellites as well as beyond-Earth missions with hyperspectral instruments.

  10. Effectiveness of Intrusion Prevention Systems (IPS) in Fast Networks

    Shafi, Muhammad Imran; Hayat, Sikandar; Sohail, Imran

    2010-01-01

    Computer systems are facing biggest threat in the form of malicious data which causing denial of service, information theft, financial and credibility loss etc. No defense technique has been proved successful in handling these threats. Intrusion Detection and Prevention Systems (IDPSs) being best of available solutions. These techniques are getting more and more attention. Although Intrusion Prevention Systems (IPSs) show a good level of success in detecting and preventing intrusion attempts to networks, they show a visible deficiency in their performance when they are employed on fast networks. In this paper we have presented a design including quantitative and qualitative methods to identify improvement areas in IPSs. Focus group is used for qualitative analysis and experiment is used for quantitative analysis. This paper also describes how to reduce the responding time for IPS when an intrusion occurs on network, and how can IPS be made to perform its tasks successfully without effecting network speed nega...

  11. Intrusion Detection Approach Using Connectionist Expert System

    MA Rui; LIU Yu-shu; DU Yan-hui

    2005-01-01

    In order to improve the detection efficiency of rule-based expert systems, an intrusion detection approach using connectionist expert system is proposed. The approach converts the AND/OR nodes into the corresponding neurons, adopts the three-layered feed forward network with full interconnection between layers,translates the feature values into the continuous values belong to the interval [0, 1 ], shows the confidence degree about intrusion detection rules using the weight values of the neural networks and makes uncertain inference with sigmoid function. Compared with the rule-based expert system, the neural network expert system improves the inference efficiency.

  12. Integrating Innate and Adaptive Immunity for Intrusion Detection

    Tedesco, Gianni; Aickelin, Uwe

    2010-01-01

    Network Intrusion Detection Systems (NDIS) monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDS's rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alters, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to an intrusion detection problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

  13. An Isolation Intrusion Detection System for Hierarchical Wireless Sensor Networks

    Rung-Ching Chen

    2010-03-01

    Full Text Available Normal 0 0 2 false false false MicrosoftInternetExplorer4 A wireless sensor network (WSN is a wireless network consisting of spatially distributed autonomous devices using sensors to cooperatively monitor environmental conditions, such as battlefield data and personal health information, and some environment limited resources. To avoid malicious damage is important while information is transmitted in wireless network. Thus, Wireless Intrusion Detection Systems are crucial to safe operation in wireless sensor networks. Wireless networks are subject to very different types of attacks compare to wired networks. In this paper, we propose an isolation table to detect intrusion by hierarchical wireless sensor networks and to estimate the effect of intrusion detection. The primary experiment proves that isolation table intrusion detection can prevent attacks effectively.

  14. Novel Intrusion Detection using Probabilistic Neural Network and Adaptive Boosting

    Tich Phuoc Tran; Longbing Cao; Dat Tran; Cuong Duc Nguyen

    2009-01-01

    This article applies Machine Learning techniques to solve Intrusion Detection problems withincomputer networks. Due to complex and dynamic nature of computer networks and hacking techniques, detecting malicious activities remains a challenging task for security experts, that is, currently available defense systems suffer from low detection capability and high number of false alarms. To overcome such performance limitations, we propose a novel Machine Learning algorithm, namely Boosted Subspac...

  15. An overview to Software Architecture in Intrusion Detection System

    Bahrami, Mehdi

    2012-01-01

    Network intrusion detection systems provide proactive defense against security threats by detecting and blocking attack-related traffic. This task can be highly complex, and therefore, software based network intrusion detection systems have difficulty in handling high speed links. This paper reviews of many type of software architecture in intrusion detection systems and describes the design and implementation of a high-performance network intrusion detection system that combines the use of software-based network intrusion detection sensors and a network processor board. The network processor acts as a customized load balancing splitter that cooperates with a set of modified content-based network intrusion detection sensors in processing network traffic.

  16. Intelligence Intrusion Detection Prevention Systems using Object Oriented Analysis method

    DR.K.KUPPUSAMY

    2010-12-01

    Full Text Available This paper is deliberate to provide a model for “Intelligence Intrusion Detection Prevention Systems using Object Oriented Analysis method ” , It describes the state’s overall requirements regarding the acquisition and implementation of intrusion prevention and detection systems with intelligence (IIPS/IIDS. This is designed to provide a deeper understanding of intrusion prevention and detection principles with intelligence may be responsible for acquiring, implementing or monitoring such systems in understanding the technology and strategies available.With the need for evolution, if not revolution, of current network architectures and the Internet, autonomous and spontaneous management will be a key feature of future networks and information systems. In this context, security is an essential property. It must be thought at the early stage of conception of these systems and designed to be also autonomous and spontaneous.Future networks and systems must be able to automatically configure themselves with respect to their security policies. The security policy specification must be dynamic and adapt itself to the changing environment. Those networks and systems should interoperate securely when their respective security policies are heterogeneous and possibly conflicting. They must be able to autonomously evaluate the impact of an intrusion in order to spontaneously select the appropriate and relevant response when a given intrusion is detected.Autonomous and spontaneous security is a major requirement of future networks and systems. Of course, it is crucial to address this issue in different wireless and mobile technologies available today such as RFID,Wifi, Wimax, 3G, etc. Other technologies such as ad hoc and sensor networks, which introduce new type of services, also share similar requirements for an autonomous and spontaneous management of security.Intelligence Intrusion Prevention Systems (IIPS are designed to aid in preventing the

  17. Mining Association Rules to Evade Network Intrusion in Network Audit Data

    Kamini Nalavade; B. B. Meshram

    2014-01-01

    With the growth of hacking and exploiting tools and invention of new ways of intrusion, intrusion detection and prevention is becoming the major challenge in the world of network security. The increasing network traffic and data on Internet is making this task more demanding. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not completely flawless. The false positive rates make it extremely hard to analyse and react to attacks...

  18. A Review of Intrusion Detection Technique by Soft Computing and Data Mining Approach

    Aditya Shrivastava

    2013-09-01

    Full Text Available The growth of internet technology spread a large amount of data communication. The communication of data compromised network threats and security issues. The network threats and security issues raised a problem of data integrity and loss of data. For the purpose of data integrity and loss of data before 20 year Anderson developed a model of intrusion detection system. Initially intrusion detection system work on process of satirical frequency of audit system logs. Latter on this system improved by various researchers and apply some other approach such as data mining technique, neural network and expert system. Now in current research trend of intrusion detection system used soft computing approach such as fuzzy logic, genetic algorithm and machine learning. In this paper discuss some method of data mining and soft computing for the purpose of intrusion detection. Here used KDDCUP99 dataset used for performance evaluation for this technique.

  19. Neural Network Based Intrusion Detection System for Critical Infrastructures

    Todd Vollmer; Ondrej Linda; Milos Manic

    2009-07-01

    Resiliency and security in control systems such as SCADA and Nuclear plant’s in today’s world of hackers and malware are a relevant concern. Computer systems used within critical infrastructures to control physical functions are not immune to the threat of cyber attacks and may be potentially vulnerable. Tailoring an intrusion detection system to the specifics of critical infrastructures can significantly improve the security of such systems. The IDS-NNM – Intrusion Detection System using Neural Network based Modeling, is presented in this paper. The main contributions of this work are: 1) the use and analyses of real network data (data recorded from an existing critical infrastructure); 2) the development of a specific window based feature extraction technique; 3) the construction of training dataset using randomly generated intrusion vectors; 4) the use of a combination of two neural network learning algorithms – the Error-Back Propagation and Levenberg-Marquardt, for normal behavior modeling. The presented algorithm was evaluated on previously unseen network data. The IDS-NNM algorithm proved to be capable of capturing all intrusion attempts presented in the network communication while not generating any false alerts.

  20. Perimeter intrusion detection and assessment system

    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

  1. A network-based realtime intrusion detection system

    The author first reviews the background of Intrusion Detection (ID), then discusses the models and classifications of Intrusion Detection System (IDS). After detail the basic concepts to realize network-based realtime IDS, the analysis of authors' work are presented

  2. An adaptive neural swarm approach for intrusion defense in ad hoc networks

    Cannady, James

    2011-06-01

    Wireless sensor networks (WSN) and mobile ad hoc networks (MANET) are being increasingly deployed in critical applications due to the flexibility and extensibility of the technology. While these networks possess numerous advantages over traditional wireless systems in dynamic environments they are still vulnerable to many of the same types of host-based and distributed attacks common to those systems. Unfortunately, the limited power and bandwidth available in WSNs and MANETs, combined with the dynamic connectivity that is a defining characteristic of the technology, makes it extremely difficult to utilize traditional intrusion detection techniques. This paper describes an approach to accurately and efficiently detect potentially damaging activity in WSNs and MANETs. It enables the network as a whole to recognize attacks, anomalies, and potential vulnerabilities in a distributive manner that reflects the autonomic processes of biological systems. Each component of the network recognizes activity in its local environment and then contributes to the overall situational awareness of the entire system. The approach utilizes agent-based swarm intelligence to adaptively identify potential data sources on each node and on adjacent nodes throughout the network. The swarm agents then self-organize into modular neural networks that utilize a reinforcement learning algorithm to identify relevant behavior patterns in the data without supervision. Once the modular neural networks have established interconnectivity both locally and with neighboring nodes the analysis of events within the network can be conducted collectively in real-time. The approach has been shown to be extremely effective in identifying distributed network attacks.

  3. Mining Association Rules to Evade Network Intrusion in Network Audit Data

    Kamini Nalavade

    2014-06-01

    Full Text Available With the growth of hacking and exploiting tools and invention of new ways of intrusion, intrusion detection and prevention is becoming the major challenge in the world of network security. The increasing network traffic and data on Internet is making this task more demanding. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not completely flawless. The false positive rates make it extremely hard to analyse and react to attacks. Intrusion detection systems using data mining approaches make it possible to search patterns and rules in large amount of audit data. In this paper, we represent a model to integrate association rules to intrusion detection to design and implement a network intrusion detection system. Our technique is used to generate attack rules that will detect the attacks in network audit data using anomaly detection. This shows that the modified association rules algorithm is capable of detecting network intrusions. The KDD dataset which is freely available online is used for our experimentation and results are compared. Our intrusion detection system using association rule mining is able to generate attack rules that will detect the attacks in network audit data using anomaly detection, while maintaining a low false positive rate.

  4. Network Intrusion Detection System Based On Machine Learning Algorithms

    Vipin Das

    2010-12-01

    Full Text Available Network and system security is of paramount importance in the present data communication environment. Hackers and intruders can create many successful attempts to cause the crash of the networks and web services by unauthorized intrusion. New threats and associated solutions to prevent these threats are emerging together with the secured system evolution. Intrusion Detection Systems (IDS are one of these solutions. The main function of Intrusion Detection System is to protect the resources from threats. It analyzes and predicts the behaviours of users, and then these behaviours will be considered an attack or a normal behaviour. We use Rough Set Theory (RST and Support Vector Machine (SVM to detect network intrusions. First, packets are captured from the network, RST is used to pre-process the data and reduce the dimensions. The features selected by RST will be sent to SVM model to learn and test respectively. The method is effective to decrease the space density of data. The experiments compare the results with Principal Component Analysis (PCA and show RST and SVM schema could reduce the false positive rate and increase the accuracy.

  5. Intrusion Detection Systems in Wireless Sensor Networks

    Vijay Kumar Mallarapu

    2012-01-01

    Full Text Available Wireless Sensor Networks (WSNs are a new technology foreseen to be used increasingly in the near future due to their data acquisition and data processing abilities. Security for WSNs is an area that needs to be considered in order to protect the functionality of these networks, the data they convey and the location of their members. The security models & protocols used in wired and other networks are not suited to WSNs because of their severe resource constrictions. In this paper, we describe various threats to WSN and then examine existing approaches to identify these threats. Finally, we propose an intrusion detection mechanism based on these existing approaches to identifying threats.

  6. Data Mining in Intrusion Detection: A Comparative Study of Methods, Types and Data Sets

    Chandrashekhar Azad

    2013-07-01

    Full Text Available In the era of information and communication technology, Security is an important issue. A lot of effort and finance are being invested in this sector. Intrusion detection is one of the most prominent fields in this area. Data mining in network intrusion detection can automate the network intrusion detection field with a greater efficiency. This paper presents a literature survey on intrusion detection system. The research papers taken in this literature survey are published from 2000 to 2012. We can see that almost 67 % of the research papers are focused on anomaly detection, 23 % on both anomaly and misuse detection and 10 % on misuse detection. In this literature survey statistics shows that 42 % KDD cup dataset, 20 % DARPA dataset and 38 % other datasets are used by the different researchers for testing the effectiveness of their proposed method for misuse detection, anomaly detection or both.

  7. Non-intrusive Quality Analysis of Monitoring Data

    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 ...

  8. Less is More: Data Processing with SVM for Intrusion Detection

    XIAO Hai-jun; HONG Fan; WANG Ling

    2009-01-01

    To improve the detection rate and lower down the false positive rate in intrusion detection system,dimensionality reduction is widely used in the intrusion detection system.For this purpose,a data processing (DP) with support vector machine (SVM) was built.Different from traditionally identifying the redundant data before purging the audit data by expert knowledge or utilizing different kinds of subsets of the available 41-connection attributes to build a classifier,the proposed strategy first removes the attributes whose correlation with another attribute exceeds a threshold,and then classifies two sequence samples as one class while removing either of the two samples whose similarity exceeds a threshold.The results of performance experiments showed that the strategy of DP and SVM is superior to the other existing data reduction strategies (e.g.,audit reduction,rule extraction,and feature selection),and that the detection model based on DP and SVM outperforms those based on data mining,soft computing,and hierarchical principal component analysis neural networks.

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

    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. PMID:24964780

  10. Detection and Protection Against Intrusions on Smart Grid Systems

    Ata Arvani

    2015-05-01

    Full Text Available The wide area monitoring of power systems is implemented at a central control center to coordinate the actions of local controllers. Phasor measurement units (PMUs are used for the collection of data in real time for the smart grid energy systems. Intrusion detection and cyber security of network are important requirements for maintaining the integrity of wide area monitoring systems. The intrusion detection methods analyze the measurement data to detect any possible cyber attacks on the operation of smart grid systems. In this paper, the model-based and signal-based intrusion detection methods are investigated to detect the presence of malicious data. The chi-square test and discrete wavelet transform (DWT have been used for anomaly-based detection. The false data injection attack (FDIA can be detected using measurement residual. If the measurement residual is larger than expected detection threshold, then an alarm is triggered and bad data can be identified. Avoiding such alarms in the residual test is referred to as stealth attack. There are two protection strategies for stealth attack: (1 Select a subset of meters to be protected from the attacker (2 Place secure phasor measurement units in the power grid. An IEEE 14-bus system is simulated using real time digital simulator (RTDS hardware platform for implementing attack and detection schemes.

  11. Method and system for spatial data input, manipulation and distribution via an adaptive wireless transceiver

    Wang, Ray (Inventor)

    2009-01-01

    A method and system for spatial data manipulation input and distribution via an adaptive wireless transceiver. The method and system include a wireless transceiver for automatically and adaptively controlling wireless transmissions using a Waveform-DNA method. The wireless transceiver can operate simultaneously over both the short and long distances. The wireless transceiver is automatically adaptive and wireless devices can send and receive wireless digital and analog data from various sources rapidly in real-time via available networks and network services.

  12. Data Reduction in Intrusion Alert Correlation

    Gianni, Tedesco

    2008-01-01

    Network intrusion detection sensors are usually built around low level models of network traffic. This means that their output is of a similarly low level and as a consequence, is difficult to analyze. Intrusion alert correlation is the task of automating some of this analysis by grouping related alerts together. Attack graphs provide an intuitive model for such analysis. Unfortunately alert flooding attacks can still cause a loss of service on sensors, and when performing attack graph correlation, there can be a large number of extraneous alerts included in the output graph. This obscures the fine structure of genuine attacks and makes them more difficult for human operators to discern. This paper explores modified correlation algorithms which attempt to minimize the impact of this attack.

  13. A Bayesian Networks in Intrusion Detection Systems

    M. Mehdi

    2007-01-01

    Full Text Available Intrusion detection systems (IDSs have been widely used to overcome security threats in computer networks. Anomaly-based approaches have the advantage of being able to detect previously unknown attacks, but they suffer from the difficulty of building robust models of acceptable behaviour which may result in a large number of false alarms caused by incorrect classification of events in current systems. We propose a new approach of an anomaly Intrusion detection system (IDS. It consists of building a reference behaviour model and the use of a Bayesian classification procedure associated to unsupervised learning algorithm to evaluate the deviation between current and reference behaviour. Continuous re-estimation of model parameters allows for real time operation. The use of recursive Log-likelihood and entropy estimation as a measure for monitoring model degradation related with behavior changes and the associated model update show that the accuracy of the event classification process is significantly improved using our proposed approach for reducing the missing-alarm.

  14. Intrusion Detection System in Wireless Sensor Networks: A Review

    Anush Ananthakumar; Tanmay Ganediwal; Dr. Ashwini Kunte

    2015-01-01

    The security of wireless sensor networks is a topic that has been studied extensively in the literature. The intrusion detection system is used to detect various attacks occurring on sensor nodes of Wireless Sensor Networks that are placed in various hostile environments. As many innovative and efficient models have emerged in the last decade in this area, we mainly focus our work on Intrusion detection Systems. This paper reviews various intrusion detection systems which can be broadly class...

  15. Signature Analysis of UDP Streams for Intrusion Detection using Data Mining Algorithms

    R.Sridevi; Dr.K.Lakshmi

    2010-01-01

    with the increased use of internet for a wide range of activity from simple data search to online commercial transactions, securing the network is extremely important for any organization. Intrusion detection becomes extremely important to secure the network. Conventional techniques for intrusion detection have been successfully deployed, but predictive action can help in protecting the system in the long run. Data mining techniques are being ncreasingly used to study the data streams and go...

  16. Groundwater intrusion into leaky sewer systems.

    Wittenberg, H; Aksoy, H

    2010-01-01

    Vast volumes of groundwater are drained by urban sewer systems. This unwanted flow component intrudes into sewer systems through leaky joints or connected house drains. However, unlike urban storm drainage, it has a high seasonal variation corresponding to groundwater storage and long slow recessions similar to baseflow in rivers also fed by shallow groundwater exfiltrating into the surface waters. By applying the nonlinear reservoir algorithm as used for baseflow separation from total flow in a river, groundwater flow is separated from daily measured influents to treatment plants in Lower Saxony and Baden-Württemberg, Germany and in the Terkos Lake watershed near Istanbul, Turkey. While waste water flows vary only moderately within a year, separated intruded groundwater flows show recessions and seasonal variations correlated to baseflow in neighbouring rivers. It is possible to conclude that recession characteristics of treatment plant influents allow quantification and prediction of groundwater intrusion into sewer systems. PMID:20595758

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

    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

  18. A Simulated Multiagent-Based Architecture for Intrusion Detection System

    Onashoga S. Adebukola

    2013-04-01

    Full Text Available In this work, a Multiagent-based architecture for Intrusion Detection System (MIDS is proposed to overcome the shortcoming of current Mobile Agent-based Intrusion Detection System. MIDS is divided into three major phases namely: Data gathering, Detection and the Response phases. The data gathering stage involves data collection based on the features in the distributed system and profiling. The data collection components are distributed on both host and network. Closed Pattern Mining (CPM algorithm is introduced for profiling users’ activities in network database. The CPM algorithm is built on the concept of Frequent Pattern-growth algorithm by mining a prefix-tree called CPM-tree, which contains only the closed itemsets and its associated support count. According to the administrator’s specified thresholds, CPM-tree maintains only closed patterns online and incrementally outputs the current closed frequent pattern of users’ activities in real time. MIDS makes use of mobile and static agents to carry out the functions of intrusion detection. Each of these agents is built with rule-based reasoning to autonomously detect intrusions. Java 1.1.8 is chosen as the implementation language and IBM’s Java based mobile agent framework, Aglet 1.0.3 as the platform for running the mobile and static agents. In order to test the robustness of the system, a real-time simulation is carried out on University of Agriculture, Abeokuta (UNAAB network dataset and the results showed an accuracy of 99.94%, False Positive Rate (FPR of 0.13% and False Negative Rate (FNR of 0.04%. This shows an improved performance of MIDS when compared with other known MA-IDSs.

  19. Intrusion Detection in Computer Networks using a Fuzzy-Heuristic Data Mining Technique

    Hamid Saadi

    2015-12-01

    Full Text Available In this article the use of Simulated Annealing (SA algorithm for creating a consistent intrusion detection system is presented. The ability of fuzzy systems to solve different types of problems has been demonstrated in several previous studies. Simulated Annealing based Fuzzy Intrusion Detection System (SAF-IDS crosses the estimated cognitive method of fuzzy systems with the learning capability of SA. The objective of this paper is to prove the ability of SAF-IDS to deal with intrusion detection classification problem as a new real-world application area which is not previously undertook with SA-based fuzzy system. Here, the use of SA is an effort to efficiently explore and exploit the large examines space usually related with the intrusion detection problem, and finds the optimum set of fuzzy if-then rules. The proposed SAF-IDS would be capable of extracting precise fuzzy classification rules from network traffic data and relates them to detect normal and invasive actions in computer networks. Tests were performed with KDD-Cup99 intrusion detection benchmark which is widely used to calculate intrusion detection algorithms. Results indicate that SAF-IDS provides more accurate intrusion detection system than several well-known and new classification algorithms.

  20. Information adaptive system of NEEDS. [of NASA End to End Data System

    Howle, W. M., Jr.; Kelly, W. L.

    1979-01-01

    The NASA End-to-End Data System (NEEDS) program was initiated by NASA to improve significantly the state of the art in acquisition, processing, and distribution of space-acquired data for the mid-1980s and beyond. The information adaptive system (IAS) is a program element under NEEDS Phase II which addresses sensor specific processing on board the spacecraft. The IAS program is a logical first step toward smart sensors, and IAS developments - particularly the system components and key technology improvements - are applicable to future smart efforts. The paper describes the design goals and functional elements of the IAS. In addition, the schedule for IAS development and demonstration is discussed.

  1. Intelligence Intrusion Detection Prevention Systems using Object Oriented Analysis method

    DR.K.KUPPUSAMY; S. Murugan

    2010-01-01

    This paper is deliberate to provide a model for “Intelligence Intrusion Detection Prevention Systems using Object Oriented Analysis method ” , It describes the state’s overall requirements regarding the acquisition and implementation of intrusion prevention and detection systems with intelligence (IIPS/IIDS). This is designed to provide a deeper understanding of intrusion prevention and detection principles with intelligence may be responsible for acquiring, implementing or monitoring such sy...

  2. Adaptation of a Data Acquisition System for Monitoring Air Quality and Radioactivity

    the main aim from this work is adapting the data acquisition system for monitoring air quality and radioactivity to save cost, time and effort. the adaptation processes are not only based on rectifying drawbacks but also modifying new features for both systems.these drawbacks are hardware problems and software problems for both systems which cause more operation cost, more operation time and more human effort these new features are modified to achieve the grown user requirements, better performance, more flexibility for customization and better user acceptance the adaptation method is implemented by determining: how exactly two systems work, components for each system and relationships between them, which components need adaptation, and finally suitable adaptation procedure for each component with maintaining the relationships between them the proposed systems overcome the above-mentioned drawbacks associated with the old systems and have new facilities to verify their main goals

  3. A survey on RBF Neural Network for Intrusion Detection System

    Henali Sheth

    2014-12-01

    Full Text Available Network security is a hot burning issue nowadays. With the help of technology advancement intruders or hackers are adopting new methods to create different attacks in order to harm network security. Intrusion detection system (IDS is a kind of security software which inspects all incoming and outgoing network traffic and it will generate alerts if any attack or unusual behavior is found in a network. Various approaches are used for IDS such as data mining, neural network, genetic and statistical approach. Among this Neural Network is more suitable approach for IDS. This paper describes RBF neural network approach for Intrusion detection system. RBF is a feed forward and supervise technique of neural network.RBF approach has good classification ability but its performance depends on its parameters. Based on survey we find that RBF approach has some short comings. In order to overcome this we need to do proper optimization of RBF parameters.

  4. Anomaly-based intrusion detection for SCADA systems

    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)

  5. Fuzzy Approach for Intrusion Detection System: A Survey

    Partha Sarathi Bhattacharjee; Dr. Shahin Ara Begum

    2013-01-01

    Secured data communication over internet and any other network is always under threat of intrusions and misuses. Intrusions pose a serious security threat for the stability and the security of information in a network environment. An intrusion is defined as any set of actions that attempt to compromise the integrity, confidentiality or availability of a resource. It includes attempting to destabilize the network, gaining unauthorized accessto files with privileges, or mishandling and misusing...

  6. Cluster Based Cost Efficient Intrusion Detection System For Manet

    Kumarasamy, Saravanan; B, Hemalatha; P, Hashini

    2013-01-01

    Mobile ad-hoc networks are temporary wireless networks. Network resources are abnormally consumed by intruders. Anomaly and signature based techniques are used for intrusion detection. Classification techniques are used in anomaly based techniques. Intrusion detection techniques are used for the network attack detection process. Two types of intrusion detection systems are available. They are anomaly detection and signature based detection model. The anomaly detection model uses the historica...

  7. Fuzzy Based Anomaly Intrusion Detection System for Clustered WSN

    Sumathy Murugan; Sundara Rajan, M.

    2015-01-01

    In Wireless Sensor Networks (WSN), the intrusion detection technique may result in increased computational cost, packet loss, performance degradation and so on. In order to overcome these issues, in this study, we propose a fuzzy based anomaly intrusion detection system for clustered WSN. Initially the cluster heads are selected based on the parameters such as link quality, residual energy and coverage. Then the anomaly intrusion is detected using fuzzy logic technique. This technique conside...

  8. Intrusion Awareness Based on Data Fusion and SVM Classification

    Ramnaresh Sharma

    2012-06-01

    Full Text Available Network intrusion awareness is important factor for risk analysis of network security. In the current decade various method and framework are available for intrusion detection and security awareness. Some method based on knowledge discovery process and some framework based on neural network. These entire model take rule based decision for the generation of security alerts. In this paper we proposed a novel method for intrusion awareness using data fusion and SVM classification. Data fusion work on the biases of features gathering of event. Support vector machine is super classifier of data. Here we used SVM for the detection of closed item of ruled based technique. Our proposed method simulate on KDD1999 DARPA data set and get better empirical evaluation result in comparison of rule based technique and neural network model.

  9. An Adaptive Fuzzy Framework based on Optimized Fuzzy Contexts for Detecting Network Intrusions

    Habib Ullah Baig

    2010-10-01

    Full Text Available Anomaly based Intrusion Detection System (AIDS is one of the key component of a reliable security infrastructure. Working at second line of defense, detection accuracy is the key objective that largely depends upon the precision of its normal profile. Due to existence of vague boundaries between normal and anomalous classes and dynamic network behavior, building accurate and generalize normal profile is very difficult. Based on the assumption that intruder?s behavior can be grouped into different phases active at different times, this article proposes to evolve and use ?short-term fuzzy profiles/contexts? for each such individual intrusion phase resulting in enhanced detection accuracy for low-level attacks. The result is a context-driven, adaptable implementation framework based on a double layer hierarchy of fuzzy sensors. The framework adapts to network conditions by switching between different contexts, according to network traffic patterns, anomaly conditions and organization?s security policies. These contexts are evolved in incremental fashion with genetic algorithm using real-time network traces. The framework is tested using DARPA 98/99 dataset showing accurate detection of low-level DoS attack.

  10. Design Network Intrusion Detection System using hybrid Fuzzy-Neural Network

    muna mhammad taher jawhar & Monica Mehrotra

    2010-08-01

    Full Text Available As networks grow both in importance and size, there is an increasing need for effective security monitors such as Network Intrusion Detection System to prevent such illicit accesses. Intrusion Detection Systems technology is an effective approach in dealing with the problems of network security. In this paper, we present an intrusion detection model based on hybrid fuzzy logic and neural network. The key idea is to take advantage of different classification abilities of fuzzy logic and neural network for intrusion detection system. The new model has ability to recognize an attack, to differentiate one attack from another i.e. classifying attack, and the most important, to detect new attacks with high detection rate and low false negative. Training and testing data were obtained from the Defense Advanced Research Projects Agency (DARPA intrusion detection evaluation data set.

  11. HYBRID FEATURE SELECTION ALGORITHM FOR INTRUSION DETECTION SYSTEM

    Seyed Reza Hasani

    2014-01-01

    Full Text Available Network security is a serious global concern. Usefulness Intrusion Detection Systems (IDS are increasing incredibly in Information Security research using Soft computing techniques. In the previous researches having irrelevant and redundant features are recognized causes of increasing the processing speed of evaluating the known intrusive patterns. In addition, an efficient feature selection method eliminates dimension of data and reduce redundancy and ambiguity caused by none important attributes. Therefore, feature selection methods are well-known methods to overcome this problem. There are various approaches being utilized in intrusion detections, they are able to perform their method and relatively they are achieved with some improvements. This work is based on the enhancement of the highest Detection Rate (DR algorithm which is Linear Genetic Programming (LGP reducing the False Alarm Rate (FAR incorporates with Bees Algorithm. Finally, Support Vector Machine (SVM is one of the best candidate solutions to settle IDSs problems. In this study four sample dataset containing 4000 random records are excluded randomly from this dataset for training and testing purposes. Experimental results show that the LGP_BA method improves the accuracy and efficiency compared with the previous related research and the feature subcategory offered by LGP_BA gives a superior representation of data.

  12. Intrusion Awareness Based on Data Fusion and SVM Classification

    Ramnaresh Sharma

    2012-06-01

    Full Text Available Network intrusion awareness is important factor forrisk analysis of network security. In the currentdecade various method and framework are availablefor intrusion detection and security awareness.Some method based on knowledge discovery processand some framework based on neural network.These entire model take rule based decision for thegeneration of security alerts. In this paper weproposed a novel method for intrusion awarenessusing data fusion and SVM classification. Datafusion work on the biases of features gathering ofevent. Support vector machine is super classifier ofdata. Here we used SVM for the detection of closeditem of ruled based technique. Our proposedmethod simulate on KDD1999 DARPA data set andget better empirical evaluation result in comparisonof rule based technique and neural network model.

  13. Fuzzy logic based Adaptive Modulation Using Non Data Aided SNR Estimation for OFDM system

    K.SESHADRI SASTRY

    2010-06-01

    Full Text Available As demand for high quality transmission increases increase of spectrum efficiency and an improvement of error performance in wireless communication systems are important . One of the promising approaches to 4G is adaptive OFDM (AOFDM . Fixed modulation systems uses only one type of modulation scheme (or order, so that either performance or capacity should be compromised Adaptive modulated systems are superior to fixed modulated systems, since they change modulation order depending on present SNR. In an adaptive modulation system SNR estimation is important since performance of adaptive modulated system depends of estimated SNR. Non-data-Aided (NDA SNR estimation systems are gaining importance in recent days since they estimate SNR range and requires less data as input .In this paper we propose an adaptive modulated OFDM system which uses NDA(Non-data Aided SNR estimation using fuzzy logic interface.The proposed system is simulated in Matlab 7.4 and The results of computer simulation show the improvement in system capacity .

  14. Reconfigurable Hardware Architecture for Network Intrusion Detection System

    A. Kaleel Rahuman

    2012-01-01

    Full Text Available Intrusion rule processing in reconfigurable hardware enables intrusion detection and prevention. The use of reconfigurable hardware for network security applications has great strides as Field Programmable Gate Array (FPGA devices have provided larger and faster resources. This proposes architecture called “BV-TCAM” is presented, which is implemented for an FPGA-based Network Intrusion Detection Systems (NIDS. The BV-TCAM architecture combines the Ternary Content Addressable Memory (TCAM and Bit Vector (BV algorithm to effectively compress the data representation and throughput. A tree bitmap implementation of the BV algorithm is used for source and destination port lookup while a TCAM performs lookup for other header fields, which can be represented as a prefix or exact value. With the aid of small embedded TCAM, packet classification can be implemented in relatively small part of the available logic of an FPGA. The BV-TCAM architecture has been modelled by VHDL. Simulations were performed by MODELSIM. This architecture have to be synthesized and implement our design using Xilinx FPGA device."

  15. Efficient Hybrid Network (Wired and Wireless Intrusion Detection using Statistical Data Streams and Detection of Clustered Alerts

    M. Thangavel

    2011-01-01

    Full Text Available Problem statement: Wireless LAN IEEE 802.11 protocols are growing rapidly and security has always been a concern with the security of wired network. Wireless networks encountered threats from unauthorized access to network resources, installation of access points and illegal sniffing (refer as classical intrusion threats. In its current hybrid wired and wireless network attacks on the generally distinguish from normal cable intrusion attacks, selective forwarding attacks, MAC spoofing attacks. This means that the simple traditional misuse detection and anomaly detection model alone not sufficient to identify these mixed attacks on the hybrid network (wired and wireless. Approach: Our proposed work presents a hybrid cluster-based intrusion detection statistical anomaly, for detecting selective forwarding in wireless networks and intrusion into traditional wired networks. The detection was identified by changes in the statistical characteristics of data traffic on the wireless network. The clustering of data traffic based on the characteristics of alert classes and normal classes improve the performance of our hybrid intrusion detection in both wired and wireless network efficiently. The simulation was performed to evaluate the performance of wired intrusion detection systems to the proposed wireless intrusion detection on the data traffic in the area of wired and wireless hybrid network environment. Results: The proposed wireless intrusion detection system sharply detect the statistical change point detection of intrusion behavior in terms of attack rate and throughput of data traffic. The probability of intrusion attack and detection delay were measured in the simulation scenario, the result is 17% better than the current part of the exiting wired intrusion detection. Conclusion: The proposed anomaly intrusion traffic detection scheme performs better in heterogametic hybrid network (i.e., wired and wireless compared to that of conventional

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

    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.

  17. Cross Layer Intrusion Detection System for Wireless Sensor Network

    Djallel Eddine Boubiche; Azeddine Bilami

    2012-01-01

    The wireless sensor networks (WSN) are particularly vulnerable to various attacks at different layers of the protocol stack. Many intrusion detection system (IDS) have been proposed to secure WSNs. But all these systems operate in a single layer of the OSI model, or do not consider the interaction and collaboration between these layers. Consequently these systems are mostly inefficient and would drain out the WSN. In this paper we propose a new intrusion detection system based on cross layer...

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

    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.

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

    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

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

    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.

  1. Intrusion Detection System using Support Vector Machine (SVM and Particle Swarm Optimization (PSO

    Vitthal Manekar

    2014-09-01

    Full Text Available Security and privacy of a system is vulnerable, when an intrusion happens. Intrusion Detection System (IDS takes an important role in network security as it detects various types of attacks in the network. In this paper, the propose Intrusion Detection System using data mining technique: SVM (Support Vector Machine and PSO (Particle Swarm Optimization. Here, first PSO performed parameter optimization using SVM to get the optimized value of C (cost and g (gamma parameter. Then PSO performed feature optimization to get optimized feature. Then these parameters and features are given to SVM to get higher accuracy. The experiment is performed by using NSL-KDD dataset.

  2. Survey on Host and Network Based Intrusion Detection System

    Niva Das

    2014-09-01

    Full Text Available With invent of new technologies and devices, Intrusion has become an area of concern because of security issues, in the ever growing area of cyber-attack. An intrusion detection system (IDS is defined as a device or software application which monitors system or network activities for malicious activities or policy violations. It produces reports to a management station [1]. In this paper we are mainly focused on different IDS concepts based on Host and Network systems.

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

    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...

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

    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...

  5. AdiosStMan: Parallelizing Casacore Table Data System using Adaptive IO System

    Wang, R.; Harris, C.; Wicenec, A.

    2016-07-01

    In this paper, we investigate the Casacore Table Data System (CTDS) used in the casacore and CASA libraries, and methods to parallelize it. CTDS provides a storage manager plugin mechanism for third-party developers to design and implement their own CTDS storage managers. Having this in mind, we looked into various storage backend techniques that can possibly enable parallel I/O for CTDS by implementing new storage managers. After carrying on benchmarks showing the excellent parallel I/O throughput of the Adaptive IO System (ADIOS), we implemented an ADIOS based parallel CTDS storage manager. We then applied the CASA MSTransform frequency split task to verify the ADIOS Storage Manager. We also ran a series of performance tests to examine the I/O throughput in a massively parallel scenario.

  6. Novel hybrid intrusion detection system for clustered wireless sensor network

    Sedjelmaci, Hichem

    2011-01-01

    Wireless sensor network (WSN) is regularly deployed in unattended and hostile environments. The WSN is vulnerable to security threats and susceptible to physical capture. Thus, it is necessary to use effective mechanisms to protect the network. It is widely known, that the intrusion detection is one of the most efficient security mechanisms to protect the network against malicious attacks or unauthorized access. In this paper, we propose a hybrid intrusion detection system for clustered WSN. Our intrusion framework uses a combination between the Anomaly Detection based on support vector machine (SVM) and the Misuse Detection. Experiments results show that most of routing attacks can be detected with low false alarm.

  7. Adaptive-array Electron Cyclotron Emission diagnostics using data streaming in a Software Defined Radio system

    Measurement of the Electron Cyclotron Emission (ECE) spectrum is one of the most popular electron temperature diagnostics in nuclear fusion plasma research. A 2-dimensional ECE imaging system was developed with an adaptive-array approach. A radio-frequency (RF) heterodyne detection system with Software Defined Radio (SDR) devices and a phased-array receiver antenna was used to measure the phase and amplitude of the ECE wave. The SDR heterodyne system could continuously measure the phase and amplitude with sufficient accuracy and time resolution while the previous digitizer system could only acquire data at specific times. Robust streaming phase measurements for adaptive-arrayed continuous ECE diagnostics were demonstrated using Fast Fourier Transform (FFT) analysis with the SDR system. The emission field pattern was reconstructed using adaptive-array analysis. The reconstructed profiles were discussed using profiles calculated from coherent single-frequency radiation from the phase array antenna

  8. Adaptive top-down suppression of hippocampal activity and the purging of intrusive memories from consciousness.

    Benoit, Roland G; Hulbert, Justin C; Huddleston, Ean; Anderson, Michael C

    2015-01-01

    When reminded of unwanted memories, people often attempt to suppress these experiences from awareness. Prior work indicates that control processes mediated by the dorsolateral prefrontal cortex (DLPFC) modulate hippocampal activity during such retrieval suppression. It remains unknown whether this modulation plays a role in purging an intrusive memory from consciousness. Here, we combined fMRI and effective connectivity analyses with phenomenological reports to scrutinize a role for adaptive top-down suppression of hippocampal retrieval processes in terminating mnemonic awareness of intrusive memories. Participants either suppressed or recalled memories of pictures depicting faces or places. After each trial, they reported their success at regulating awareness of the memory. DLPFC activation was greatest when unwanted memories intruded into consciousness and needed to be purged, and this increased engagement predicted superior control of intrusive memories over time. However, hippocampal activity was decreased during the suppression of place memories only. Importantly, the inhibitory influence of the DLPFC on the hippocampus was linked to the ensuing reduction in intrusions of the suppressed memories. Individuals who exhibited negative top-down coupling during early suppression attempts experienced fewer involuntary memory intrusions later on. Over repeated suppressions, the DLPFC-hippocampus connectivity grew less negative with the degree that they no longer had to purge unwanted memories from awareness. These findings support a role of DLPFC in countermanding the unfolding recollection of an unwanted memory via the suppression of hippocampal processing, a mechanism that may contribute to adaptation in the aftermath of traumatic experiences. PMID:25100219

  9. A real time OCSVM Intrusion Detection module with low overhead for SCADA systems

    Leandros A. Maglaras

    2014-10-01

    Full Text Available In this paper we present a intrusion detection module capable of detecting malicious network traffic in a SCADA (Supervisory Control and Data Acquisition system. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM (One-Class Support Vector Machine is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automate SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detect anomalies in the system real time. In order to decrease the overhead induced by communicated alarms we propose a new detection mechanism that is based on the combination of OCSVM with a recursive k-means clustering procedure. The proposed intrusion detection module K??OCSVMis capable to distinguish severe alarms from possible attacks regardless of the values of parameters and , making it ideal for real-time intrusion detection mechanisms for SCADA systems. The most severe alarms are then communicated with the use of IDMEF files to an IDSIDS (Intrusion Detection System system that is developed under CockpitCI project. Alarm messages carry information about the source of the incident, the time of the intrusion and a classification of the alarm.

  10. A Multi-Dimensional approach towards Intrusion Detection System

    Thakur, Manoj Rameshchandra

    2012-01-01

    In this paper, we suggest a multi-dimensional approach towards intrusion detection. Network and system usage parameters like source and destination IP addresses; source and destination ports; incoming and outgoing network traffic data rate and number of CPU cycles per request are divided into multiple dimensions. Rather than analyzing raw bytes of data corresponding to the values of the network parameters, a mature function is inferred during the training phase for each dimension. This mature function takes a dimension value as an input and returns a value that represents the level of abnormality in the system usage with respect to that dimension. This mature function is referred to as Individual Anomaly Indicator. Individual Anomaly Indicators recorded for each of the dimensions are then used to generate a Global Anomaly Indicator, a function with n variables (n is the number of dimensions) that provides the Global Anomaly Factor, an indicator of anomaly in the system usage based on all the dimensions consid...

  11. Novel hybrid intrusion detection system for clustered wireless sensor network

    Hichem Sedjelmaci; Mohamed Feham

    2011-01-01

    Wireless sensor network (WSN) is regularly deployed in unattended and hostile environments. The WSN is vulnerable to security threats and susceptible to physical capture. Thus, it is necessary to use effective mechanisms to protect the network. It is widely known, that the intrusion detection is one of the most efficient security mechanisms to protect the network against malicious attacks or unauthorized access. In this paper, we propose a hybrid intrusion detection system for clustered WSN. ...

  12. The design about the intrusion defense system for IHEP

    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

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

    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.

  14. Intrusion Prevention/Intrusion Detection System (IPS/IDS) for Wifi Networks

    Michal Korcak; Jaroslav Lamer; Frantisek Jakab

    2014-01-01

    The nature of wireless networks itself created new vulnerabilities that in the classical wired network s do not exist. This results in an evolutional requireme nt to implement new sophisticated security mechanis m in form of Intrusion Detection and Prevention Systems. This paper deals with security issues of small off ice and home office wireless networks. The goal of our work is to design and evaluate wireless IDPS with u se of packet injection method. Dec...

  15. Mining Techniques in Network Security to Enhance Intrusion Detection Systems

    Maher Salem

    2012-12-01

    Full Text Available In intrusion detection systems, classifiers still suffer from several drawbacks such as data dimensionalityand dominance, different network feature types, and data impact on the classification. In this paper twosignificant enhancements are presented to solve these drawbacks. The first enhancement is an improvedfeature selection using sequential backward search and information gain. This, in turn, extracts valuablefeatures that enhance positively the detection rate and reduce the false positive rate. The secondenhancement is transferring nominal network features to numeric ones by exploiting the discrete randomvariable and the probability mass function to solve the problem of different feature types, the problem ofdata dominance, and data impact on the classification. The latter is combined to known normalizationmethods to achieve a significant hybrid normalization approach. Finally, an intensive and comparativestudy approves the efficiency of these enhancements and shows better performance comparing to otherproposed methods.

  16. Data reduction in the ITMS system through a data acquisition model with self-adaptive sampling rate

    Ruiz, M. [Grupo de Investigacion en Instrumentacion y Acustica Aplicada, Universidad Politecnica de Madrid (UPM), Crta. Valencia Km-7, Madrid 28031 (Spain)], E-mail: mariano.ruiz@upm.es; Lopez, JM.; Arcas, G. de [Grupo de Investigacion en Instrumentacion y Acustica Aplicada, Universidad Politecnica de Madrid (UPM), Crta. Valencia Km-7, Madrid 28031 (Spain); Barrera, E. [Departamento de Sistemas Electronicos y de Control, Universidad Politecnica de Madrid (UPM), Crta. Valencia Km-7, Madrid 28031 (Spain); Melendez, R. [Grupo de Investigacion en Instrumentacion y Acustica Aplicada, Universidad Politecnica de Madrid (UPM), Crta. Valencia Km-7, Madrid 28031 (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain)

    2008-04-15

    Long pulse or steady state operation of fusion experiments require data acquisition and processing systems that reduce the volume of data involved. The availability of self-adaptive sampling rate systems and the use of real-time lossless data compression techniques can help solve these problems. The former is important for continuous adaptation of sampling frequency for experimental requirements. The latter allows the maintenance of continuous digitization under limited memory conditions. This can be achieved by permanent transmission of compressed data to other systems. The compacted transfer ensures the use of minimum bandwidth. This paper presents an implementation based on intelligent test and measurement system (ITMS), a data acquisition system architecture with multiprocessing capabilities that permits it to adapt the system's sampling frequency throughout the experiment. The sampling rate can be controlled depending on the experiment's specific requirements by using an external dc voltage signal or by defining user events through software. The system takes advantage of the high processing capabilities of the ITMS platform to implement a data reduction mechanism based in lossless data compression algorithms which are themselves based in periodic deltas.

  17. Intrusion problematic during water supply systems' operation

    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.

  18. System and method for adaptively deskewing parallel data signals relative to a clock

    Jenkins, Philip Nord; Cornett, Frank N.

    2011-10-04

    A system and method of reducing skew between a plurality of signals transmitted with a transmit clock is described. Skew is detected between the received transmit clock and each of received data signals. Delay is added to the clock or to one or more of the plurality of data signals to compensate for the detected skew. The delay added to each of the plurality of delayed signals is updated to adapt to changes in detected skew.

  19. Cross Layer Intrusion Detection System for Wireless Sensor Network

    Djallel Eddine Boubiche

    2012-03-01

    Full Text Available The wireless sensor networks (WSN are particularly vulnerable to various attacks at different layers of the protocol stack. Many intrusion detection system (IDS have been proposed to secure WSNs. But all these systems operate in a single layer of the OSI model, or do not consider the interaction and collaboration between these layers. Consequently these systems are mostly inefficient and would drain out the WSN. In this paper we propose a new intrusion detection system based on cross layer interaction between the network, Mac and physical layers. Indeed we have addressed the problem of intrusion detection in a different way in which the concept of cross layer is widely used leading to the birth of a new type of IDS. We have experimentally evaluated our system using the NS simulator to demonstrate itseffectiveness in detecting different types of attacks at multiple layers of the OSI model.

  20. NASA End-to-End Data System /NEEDS/ information adaptive system - Performing image processing onboard the spacecraft

    Kelly, W. L.; Howle, W. M.; Meredith, B. D.

    1980-01-01

    The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onbaord image processing. Since the IAS is a data preprocessing system which is closely coupled to the sensor system, it serves as a first step in providing a 'Smart' imaging sensor. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner and provide the opportunity to design sensor systems which can be reconfigured in near real time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

  1. Semantic intrusion detection with multisensor data fusion using complex event processing

    R Bhargavi; V Vaidehi

    2013-04-01

    Complex Event Processing (CEP) is an emerging technology for processing and identifying patterns of interest from multiple streams of events in real/near real time. Sensor network-based security and surveillance is a topic of recent research where events generated from distributed sensors at an unpredictable rate need to be analysed for possible threats and respond in a timely manner. Traditional software architectures like client/server architecture where the interactions are pull-based (DBMS) do not target the efficient processing of streams of events in real time. CEP which is a push-based system can process streaming data to identify the intrusion patterns in near real time and respond to the threats. An Intrusion Detection System (IDS) based on single sensor may fail to give accurate identification of intrusion. Hence there is a need for multisensor based IDS. A multisensor-based IDS enables identification of the intrusion patterns semantically by correlating the events and context information provided by multiple sensors. JDL multisource data fusion model is a well-known research model first established by the Joint Directorate Laboratories. This paper proposes JDL fusion framework-based CEP for semantic intrusion detection. The events generated from heterogeneous sensors are collected, aggregated using logical and spatiotemporal relations to form complex events which model the intrusion patterns. The proposed system is implemented and the results show that the proposed system out performs the pull-based solutions in terms of detection accuracy and detection time.

  2. The System Design of a Node of P2P Networks for Intrusion Detection

    Lei Ding

    2013-08-01

    Full Text Available To improve the measuring accuracy of intrusion detection, a system design of a node for intrusion detection is proposed in this paper. First, the technology that applies the traditional intrusion detection method, such as anomaly detection and misuse detection, into P2P networks is presented. Next, to build the trust relationship among the nodes, and realize the cooperation mechanism of data detection, collection and response among the nodes of P2P networks, the corresponding solving plans, such as topological structure, trust model, information share and information fusion, are proposed in this paper. Then the concept of network telescope is presented to broaden the field of vision of malicious attacks and abnormal network packets in the propagation path. Finally, a system design of a node for intrusion detection using the honeypot technology is proposed in this paper.

  3. AGENT BASED INTRUSION DETECTION SYSTEM IN MANET

    J. K. Mandal

    2013-02-01

    Full Text Available In this paper a technique for intrusion detection in MANET has been proposed where agents are fired from a node which traverses each node randomly and detect the malicious node. Detection is based on triangular encryption technique (TE where AODV is taken as routing protocol. For simulation we have taken NS2 (2.33 where two type of parameters are considered out of which number of nodes and percentage of node mobility are the attributes. For analysis purpose 20, 30, 30, 40, 50 and 60 nodes are taken with a variable percentage of malicious node as 0 %( no malicious, 10%, 20%, 30% and 40%. Analysis have been done taking generated packets, forwarded packets, delay, and average delay as parameters

  4. Protecting coastal abstraction boreholes from seawater intrusion using self-potential data

    Graham, Malcolm; Butler, Adrian; MacAllister, Donald John; Vinogradov, Jan; Ijioma, Amadi; Jackson, Matthew

    2016-04-01

    We investigate whether the presence and transport of seawater can influence self-potentials (SPs) measured within coastal groundwater boreholes, with a view to using SP monitoring as part of an early warning system for saline intrusion. SP data were collected over a period of 18 months from a coastal groundwater borehole in the fractured Chalk of England. Spectral analysis of the results shows semi-diurnal fluctuations that are several orders of magnitude higher than those observed from monitoring of the Chalk more than 60 km inland, indicating a strong influence from oceanic tides. Hydrodynamic and geoelectric modelling of the coastal aquifer suggests that observed pressure changes (giving rise to the streaming potential) are not sufficient to explain the magnitude of the observed SP fluctuations. Simulation of the exclusion-diffusion potential, produced by changes in concentration across the saline front, is required to match the SP data from the borehole, despite the front being located some distance away. In late summer of 2013 and 2014, seawater intrusion occurred in the coastal monitoring borehole. When referenced to the shallowest borehole electrode, there was a characteristic increase in SP within the array, several days before any measurable increase in salinity. The size of this precursor increased steadily with depth, typically reaching values close to 0.3 mV in the deepest electrode. Numerical modelling suggests that the exclusion-diffusion potential can explain the magnitude of the precursor, but that the polarity of the change in SP cannot be replicated assuming a homogeneous aquifer. Small-scale models of idealised Chalk blocks were used to simulate the effects of discrete fractures on the distribution of SP. Initial results suggest that comparatively large reductions in voltage can develop in the matrix ahead of the front, in conjunction with a reduced or absent precursor in the vicinity of a fracture. Geophysical logging indicates the presence of a

  5. Intrusion Prevention/Intrusion Detection System (IPS/IDS for Wifi Networks

    Michal Korcak

    2014-07-01

    Full Text Available The nature of wireless networks itself created new vulnerabilities that in the classical wired network s do not exist. This results in an evolutional requireme nt to implement new sophisticated security mechanis m in form of Intrusion Detection and Prevention Systems. This paper deals with security issues of small off ice and home office wireless networks. The goal of our work is to design and evaluate wireless IDPS with u se of packet injection method. Decrease of attacker’s traffic by 95% was observed when compared to attacker’s traffic without deployment of proposed I DPS system.

  6. LKM: A LDA-Based K-Means Clustering Algorithm for Data Analysis of Intrusion Detection in Mobile Sensor Networks

    Yuhua Zhang; Kun Wang; Min Gao; Zhiyou Ouyang; Siguang Chen

    2015-01-01

    Mobile sensor networks (MSNs), consisting of mobile nodes, are sensitive to network attacks. Intrusion detection system (IDS) is a kind of active network security technology to protect network from attacks. In the data gathering phase of IDS, due to the high-dimension data collected in multidimension space, great pressure has been put on the subsequent data analysis and response phase. Therefore, traditional methods for intrusion detection can no longer be applicable in MSNs. To improve the p...

  7. Network Intrusion Detection Evading System using Frequent Pattern Matching

    N. B. Dhurpate#1 , L.M.R.J. Lobo

    2013-08-01

    Full Text Available Signature based NIDS are efficient at detecting attacks for what they are prepared for. This makes an intruderto focus on the new evasion technique to remain undetected. Emergence of new evasion technique may cause NIDS to fail. Unfortunately, most of these techniques are based on network protocols ambiguities, so NIDS designers must take them into account when updating their tools. This paper presents a framework for evading network intrusion detection system and detection over NIDS using frequent element pattern matching. The core of the framework is to model the NIDS using Adaboost algorithm that allows the understanding of how the NIDS classifies network data. We look for some way of evading the NIDS detection by changing some of the fields of the packets. We use publicly available dataset (KDD-99 for showing the proof of our concept. For real time evasion detection NIDS is build with Apriori algorithm to analyze NIDS robustness with high detection rate accuracy

  8. NEEDS - Information Adaptive System

    Kelly, W. L.; Benz, H. F.; Meredith, B. D.

    1980-01-01

    The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onboard image processing. The IAS is a data preprocessing system which is closely coupled to the sensor system. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner, and provide the opportunity to design sensor systems which can be reconfigured in near real-time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

  9. A new data normalization method for unsupervised anomaly intrusion detection

    Long-zheng CAI; Jian CHEN; Yun KE; Tao CHEN; Zhi-gang LI

    2010-01-01

    Unsupervised anomaly detection can detect attacks without the need for clean or labeled training data.This paper studies the application of clustering to unsupervised anomaly detection(ACUAD).Data records are mapped to a feature space.Anomalies are detected by determining which points lie in the sparse regions of the feature space.A critical element for this method to be effective is the definition of the distance function between data records.We propose a unified normalization distance framework for records with numeric and nominal features mixed data.A heuristic method that computes the distance for nominal features is proposed,taking advantage of an important characteristic of nominal features-their probability distribution.Then,robust methods are proposed for mapping numeric features and computing their distance,these being able to tolerate the impact of the value difference in scale and diversification among features,and outliers introduced by intrusions.Empirical experiments with the KDD 1999 dataset showed that ACUAD can detect intrusions with relatively low false alarm rates compared with other approaches.

  10. Intrusion Detection Systems Based On Packet Sniffing

    Ushus Maria Joseph

    2013-01-01

    Full Text Available In the present era of networks, security of network systems is becoming increasingly important, as more and more sensitive information is being stored and manipulated online. The paper entitled ’Packet Sniffing’ is a IDS where it monitors packets on the network wire and attempts to the discovery of hacker/cracker who is attempting to break into system. Packet Sniffing also finds the contents and tracks the data packet in the network system. This sniffing is being performed by comparing the captured packet with the intruder details stored in the database .If the packet is found to be an intruder it is then forwarded to the firewall with the respective message for blocking. The Emotional Ants module contains the sender and receiver .The sender will inform all the other Ants running in other machines about the detection of intruder through his pheromone (Messages. The receiver in Ants will listen for the messages from other Ants

  11. Predicting Packet Transmission Data over IP Networks Using Adaptive Neuro-Fuzzy Inference Systems

    Samira Chabaa

    2009-01-01

    Full Text Available Problem statement: The statistical modeling for predicting network traffic has now become a major tool used for network and is of significant interest in many domains: Adaptive application, congestion and admission control, wireless, network management and network anomalies. To comprehend the properties of IP-network traffic and system conditions, many kinds of reports based on measured network traffic data have been reported by several researchers. The goal of the present contribution was to complement these previous researches by predicting network traffic data. Approach: The Adaptive Neuro-Fuzzy Inference System (ANFIS was realized by an appropriate combination of fuzzy systems and neural networks. It was applied in different applications which have been increased in recent years and have multidisciplinary in several domains with a high accuracy. For this reason, we used a set of input and output data of packet transmission over Internet Protocol (IP networks as input and output of ANFIS to develop a model for predicting data. Results: ANFIS was compared with some existing model based on Volterra system with Laguerre functions. The obtained results demonstrate that the sequences of generated values have the same statistical characteristics as those really observed. Furthermore, the relative error using ANFIS model was better than this obtained by Volterra system model. Conclusion: The developed model fits well real data and can be used for predicting purpose with a high accuracy.

  12. Identification Method of Attack Path Based on Immune Intrusion Detection

    Wenhua Huang

    2014-04-01

    Full Text Available This thesis takes researches on the immune intrusion detection and IP trace back technology. To find out the network data features of the real-time analyses, the distributed immune intrusion detection system and the packet marking theory are used; to guide the dynamically processing of path signs technology, the immune intrusion detection system is used; what’s more, to dynamically adaptive different methods of characteristics of network data, the path signs technology is adopted. After that, the attack paths can be quickly identified to provide path information for feature detector on attack path in the immune intrusion detection system. Experiment results show that this scheme can quickly reconstruct the attack path information, and the performance on the aspects of the convergence is with efficiency rate and false positive rate, which is superior to the current probabilistic packet marking algorithm and can provide characteristic path information for immune intrusion detection system

  13. A methodical and adaptive framework for Data Warehouse of Salary Management System

    Manzoor Ahmad

    2014-06-01

    Full Text Available Years of experience as an employee of University of Kashmir has always desired us to have a typical solution where most of the activities related to salary are fully automated without checking across the files whenever there is a need e.g. individual month‟s salary report , web based information submission, filing of returns , increment information etc. After thorough analysis , taking employee satisfaction , sensitivity and security of data , a long term solution was to develop a centralized University salary management system and its data warehouse . In this paper the design and implementation of an adaptive data warehouse is presented which supports large volume of data and saves the cost effectively. It also enable decision makers pose queries and question to the system. However decision support systems only support a set of queries and operations that are to be performed.

  14. A methodical and adaptive framework for Data Warehouse of Salary Management System

    Manzoor Ahmad

    2015-11-01

    Full Text Available Years of experience as an employee of University of Kashmir has always desired us to have a typical solution where most of the activities related to salary are fully automated without checking across the files whenever there is a need e.g. individual month‟s salary report , web based information submission, filing of returns , increment information etc. After thorough analysis , taking employee satisfaction , sensitivity and security of data , a long term solution was to develop a centralized University salary management system and its data warehouse . In this paper the design and implementation of an adaptive data warehouse is presented which supports large volume of data and saves the cost effectively. It also enable decision makers pose queries and question to the system. However decision support systems only support a set of queries and operations that are to be performed.

  15. HYBRID ARCHITECTURE FOR DISTRIBUTED INTRUSION DETECTION SYSTEM IN WIRELESS NETWORK

    Seyedeh Yasaman Rashida

    2013-06-01

    Full Text Available In order to the rapid growth of the network application, new kinds of network attacks are emerging endlessly. So it is critical to protect the networks from attackers and the Intrusion detection technology becomes popular. Therefore, it is necessary that this security concern must be articulate right from the beginning of the network design and deployment. The intrusion detection technology is the process of identifying network activity that can lead to a compromise of security policy. Lot of work has been done in detection of intruders. But the solutions are not satisfactory. In this paper, we propose a novel Distributed Intrusion Detection System using Multi Agent In order to decrease false alarms and manage misuse and anomaly detects.

  16. Nuclear data needs for non-intrusive inspection

    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

  17. Nuclear data needs for non-intrusive inspection

    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. (author)

  18. Nuclear data needs for non-intrusive inspection.

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

    2000-11-29

    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.

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

    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.

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

    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...... 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...

  1. Adaptive Lockable Units to Improve Data Availability in a Distributed Database System

    Khaled Maabreh

    2016-01-01

    Full Text Available Distributed database systems have become a phenomenon and have been considered a crucial source of information for numerous users. Users with different jobs are using such systems locally or via the Internet to meet their professional requirements. Distributed database systems consist of a number of sites connected over a computer network. Each site deals with its own database and interacts with other sites as needed. Data replication in these systems is considered a key factor in improving data availability. However, it may affect system performance when most of the transactions that access the data contain write or a mix of read and write operations because of exclusive locks and update propagation. This research proposes a new adaptive approach for increasing the availability of data contained in a distributed database system. The proposed approach suggests a new lockable unit by increasing the database hierarchy tree by one level to include attributes as lockable units instead of the entire row. This technique may allow several transactions to access the database row simultaneously by utilizing some attributes and keeping others available for other transactions. Data in a distributed database system can be accessed locally or remotely by a distributed transaction, with each distributed transaction decomposed into several sub-transactions called participants or agents. These agents access the data at multiple sites and must guarantee that any changes to the data must be committed in order to complete the main transaction. The experimental results show that using attribute-level locking will increase data availability, reliability, and throughput, as well as enhance overall system performance. Moreover, it will increase the overhead of managing such a large number of locks, which will be managed according to the qualification of the query.

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

    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.

  3. Intrusion Detection Systems in Wireless Sensor Networks

    Vijay Kumar Mallarapu; K.V.D.Sagar

    2012-01-01

    Wireless Sensor Networks (WSNs) are a new technology foreseen to be used increasingly in the near future due to their data acquisition and data processing abilities. Security for WSNs is an area that needs to be considered in order to protect the functionality of these networks, the data they convey and the location of their members. The security models & protocols used in wired and other networks are not suited to WSNs because of their severe resource constrictions. In this paper, we describ...

  4. Distributed Intrusion Detection System for Ad hoc Mobile Networks

    Muhammad Nawaz Khan

    2012-01-01

    Full Text Available In mobile ad hoc network resource restrictions on bandwidth, processing capabilities, battery life and memory of mobile devices lead tradeoff between security and resources consumption. Due to some unique properties of MANETs, proactive security mechanism like authentication, confidentiality, access control and non-repudiation are hard to put into practice. While some additional security requirements are also needed, like cooperation fairness, location confidentiality, data freshness and absence of traffic diversion. Traditional security mechanism i.e. authentication and encryption, provide a security beach to MANETs. But some reactive security mechanism is required who analyze the routing packets and also check the overall network behavior of MANETs. Here we propose a local-distributed intrusion detection system for ad hoc mobile networks. In the proposed distributed-ID, each mobile node works as a smart agent. Data collect by node locally and it analyze that data for malicious activity. If any abnormal activity discover, it informs the surrounding nodes as well as the base station. It works like a Client-Server model, each node works in collaboration with server, updating its database each time by server using Markov process. The proposed local distributed- IDS shows a balance between false positive and false negative rate. Re-active security mechanism is very useful in finding abnormal activities although proactive security mechanism present there. Distributed local-IDS useful for deep level inspection and is suited with the varying nature of the MANETs.

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

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

    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 ene...

  6. Distributed Intrusion Detection for Computer Systems Using Communicating Agents

    Ingram, Dennis J.; Kremer, H. Steven; Neil C. Rowe

    2000-01-01

    This paper appeared in the Proceedings of the 2000 Command and Control Research and Technology Symposium (CCRTS), Monterey, CA, June 11-13, 2000, and won the award for “Best Paper”. Intrusion detection for computer systems is a key problem of the Internet, and the Windows NT operating system has a number of vulnerabilities. The work presented here demonstrates that independent detection agents under Windows NT can be run in a distributed fashion, each operating mostly independent ...

  7. Usefulness of DARPA dataset for intrusion detection system evaluation

    Thomas, Ciza; Sharma, Vishwas; Balakrishnan, N.

    2008-01-01

    The MIT Lincoln Laboratory IDS evaluation methodology is a practical solution in terms of evaluating the performance of Intrusion Detection Systems, which has contributed tremendously to the research progress in that field. The DARPA IDS evaluation dataset has been criticized and considered by many as a very outdated dataset, unable to accommodate the latest trend in attacks. Then naturally the question arises as to whether the detection systems have improved beyond detecting these old level ...

  8. Optimizations of Battery-Based Intrusion Protection Systems

    Nelson, Theresa Michelle

    2008-01-01

    As time progresses, small mobile devices become more prevalent for both personal and industrial use, providing malicious network users with new and exciting venues for security exploits. Standard security applications, such as Norton Antivirus and MacAfee, require computing power, memory space, and operating system complexity that are not present in small mobile devices. Recently, the Battery-Sensing Intrusion Protection System (B-SIPS) was devised as a means to correct the inability of small...

  9. Intrusion Detection of NSM Based DoS Attacks Using Data Mining in Smart Grid

    JungChan Na; Kijoon Chae; Mihui Kim; Shi Li; Xinyi Chen; Kyung Choi

    2012-01-01

    In this paper, we analyze the Network and System Management (NSM) requirements and NSM data objects for the intrusion detection of power systems; NSM is an IEC 62351-7 standard. We analyze a SYN flood attack and a buffer overflow attack to cause the Denial of Service (DoS) attack described in NSM. After mounting the attack in our attack testbed, we collect a data set, which is based on attributes for the attack. We then run several data mining methods with the data set using the Waikato Envir...

  10. Detecting network intrusions by data mining and variable-length sequence pattern matching

    Tian Xinguang; Duan Miyi; Sun Chunlai; Liu Xin

    2009-01-01

    Anomaly detection has been an active research topic in the field of network intrusion detection for many years. A novel method is presented for anomaly detection based on system calls into the kernels of Unix or Linux systems. The method uses the data mining technique to model the normal behavior of a privileged program and uses a variable-length pattern matching algorithm to perform the comparison of the current behavior and historic normal behavior, which is more suitable for this problem than the fixed-length pattern matching algorithm proposed by Forrest et al. At the detection stage, the particularity of the audit data is taken into account, and two alternative schemes could be used to distinguish between normalities and intrusions. The method gives attention to both computational efficiency and detection accuracy and is especially applicable for on-line detection. The performance of the method is evaluated using the typical testing data set, and the results show that it is significantly better than the anomaly detection method based on hidden Markov models proposed by Yan et al. and the method based on fixed-length patterns proposed by Forrest and Hofmeyr. The novel method has been applied to practical hosted-based intrusion detection systems and achieved high detection performance.

  11. System and method for the adaptive mapping of matrix data to sets of polygons

    Burdon, David (Inventor)

    2003-01-01

    A system and method for converting bitmapped data, for example, weather data or thermal imaging data, to polygons is disclosed. The conversion of the data into polygons creates smaller data files. The invention is adaptive in that it allows for a variable degree of fidelity of the polygons. Matrix data is obtained. A color value is obtained. The color value is a variable used in the creation of the polygons. A list of cells to check is determined based on the color value. The list of cells to check is examined in order to determine a boundary list. The boundary list is then examined to determine vertices. The determination of the vertices is based on a prescribed maximum distance. When drawn, the ordered list of vertices create polygons which depict the cell data. The data files which include the vertices for the polygons are much smaller than the corresponding cell data files. The fidelity of the polygon representation can be adjusted by repeating the logic with varying fidelity values to achieve a given maximum file size or a maximum number of vertices per polygon.

  12. Hybrid Adaptive Intrusion Prevention%自适应混合入侵防御

    乔佩利; 韩伟

    2011-01-01

    This paper proposed a model of Intrusion Prevent System, which has the adaptive ability and apply a hybrid approach to host security that prevents binary code injection attacks. It incorporates three major components: an anomaly-based classifier, a signature-based filtering scheme, and a supervision framework that employs Instruction Set Randomization ( ISR ). ISR can precisely identify the injected code, the classifier and the filter via a learning mechanism based on this feedback can be tuned. Capturing the injected code allows FLIPS to construct signatures for zero-day exploits. Experimental results show that the model can discard input that is anomalous matches or malicious input, protecting the application from attack effectively.%提出一个应用混合的方法来阻止破坏主机安全的二进制代码注入式攻击并具有自适应能力的入侵防御系统模型(Feedback Leaming IPS,FLIPS).它包括三个主要组成部分:基于异常的分类器,基于签名的过滤系统,和采用指令集随机化(Instruction Set Randomization,ISR)的监管框架.ISR可以准确识别注入的代码,以这种反馈为基础对分类器和过滤器进行调整,并允许FLIPS对捕捉到的注入代码构建零日攻击签名.经试验表明,该模型能够丢弃那些匹配异常或已知的恶意输入,从而有效地保护应用程序免受攻击.

  13. Evaluating the Strengths and Weaknesses of Mining Audit Data for Automated Models for Intrusion Detection in Tcpdump and Basic Security Module Data

    A. Arul Lawrence Selvakumar

    2012-01-01

    Full Text Available Problem statement: Intrusion Detection System (IDS have become an important component of infrastructure protection mechanism to secure the current and emerging networks, its services and applications by detecting, alerting and taking necessary actions against the malicious activities. The network size, technology diversities and security policies make networks more challenging and hence there is a requirement for IDS which should be very accurate, adaptive, extensible and more reliable. Although there exists the novel framework for this requirement namely Mining Audit Data for Automated Models for Intrusion Detection (MADAM ID, it is having some performance shortfalls in processing the audit data. Approach: Few experiments were conducted on tcpdump data of DARPA and BCM audit files by applying the algorithms and tools of MADAM ID in the processing of audit data, mine patterns, construct features and build RIPPER classifiers. By putting it all together, four main categories of attacks namely DOS, R2L, U2R and PROBING attacks were simulated. Results: This study outlines the experimentation results of MADAM ID in testing the DARPA and BSM data on a simulated network environment. Conclusion: The strengths and weakness of MADAM ID has been identified thru the experiments conducted on tcpdump data and also on Pascal based audit files of Basic Security Module (BSM. This study also gives some additional directions about the future applications of MADAM ID.

  14. An Implementation Approach for Intrusion Detection System in Wireless sensor Network

    Ruchi Bhatnagar; Dr. A.K. Srivastava; Anupriya Sharma

    2010-01-01

    The Intrusion Detection System (IDS) has become a critical component of wireless sensor networks security strategy. In this paper we have made an effort to document related issues and challenges of intrusion detection system for wireless sensor network and proposed a novel secure strategy for their implementation that can detect possible intrusion in the network, alerting user after intrusion had been detected and reconfigure the network if possible.

  15. An Implementation Approach for Intrusion Detection System in Wireless sensor Network

    Ruchi Bhatnagar

    2010-10-01

    Full Text Available The Intrusion Detection System (IDS has become a critical component of wireless sensor networks security strategy. In this paper we have made an effort to document related issues and challenges of intrusion detection system for wireless sensor network and proposed a novel secure strategy for their implementation that can detect possible intrusion in the network, alerting user after intrusion had been detected and reconfigure the network if possible.

  16. A ROLE OF INTRUSION DETECTION SYSTEM FOR WIRELESS LAN USING VARIOUS SCHEMES AND RELATED ISSUES

    Kamalanaban Ethala; Seshadri, R; N. G. Renganathan; M. S. Saravanan

    2013-01-01

    The advancement in network based technology and augmented dependability of our everyday life on this technology. During recent years, number of attacks on networks has intensely increased. Hence interest in network intrusion detection has increased among the researchers. This study assesses different kinds of IDS and inclines preemptive procedures. An Intrusion Detection System (IDS) is used to automate the intrusion detection process. An Intrusion Deterrence System (IPS) is software which ha...

  17. A Novel Local Network Intrusion Detection System Based on Support Vector Machine

    Muamer N. Mohammad; Norrozila Sulaiman; Emad T Khalaf

    2011-01-01

    Problem statement: Past few years have witnessed a growing recognition of intelligent techniques for the construction of efficient and reliable Intrusion Detection Systems (IDS). Many methods and techniques were used for modeling the IDS, but some of them contribute little or not to resolve it. Approach: Intrusion detection system for local area network by using Support Vector Machines (SVM) was proposed. First, the intrusion ways and intrusion connecting of Local Area Network were defined fo...

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

    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.

  19. Network Threat Characterization in Multiple Intrusion Perspectives using Data Mining Technique

    Oluwafemi Oriola

    2012-12-01

    Full Text Available For effective security incidence response on the network, a reputable approach must be in place at bothprotected and unprotected region of the network. This is because compromise in the demilitarized zonecould be precursor to threat inside the network. The improved complexity of attacks in present times andvulnerability of system are motivations for this work. Past and present approaches to intrusion detectionand prevention have neglected victim and attacker properties despite the fact that for intrusion to occur,an overt act by an attacker and a manifestation, observable by the intended victim, which results fromthat act are required. Therefore, this paper presents a threat characterization model for attacks from thevictim and the attacker perspective of intrusion using data mining technique. The data mining techniquecombines Frequent Temporal Sequence Association Mining and Fuzzy Logic. Apriori Association Miningalgorithm was used to mine temporal rule patterns from alert sequences while Fuzzy Control System wasused to rate exploits. The results of the experiment show that accurate threat characterization in multipleintrusion perspectives could be actualized using Fuzzy Association Mining. Also, the results proved thatsequence of exploits could be used to rate threat and are motivated by victim properties and attackerobjectives.

  20. A ROLE OF INTRUSION DETECTION SYSTEM FOR WIRELESS LAN USING VARIOUS SCHEMES AND RELATED ISSUES

    Kamalanaban Ethala

    2013-01-01

    Full Text Available The advancement in network based technology and augmented dependability of our everyday life on this technology. During recent years, number of attacks on networks has intensely increased. Hence interest in network intrusion detection has increased among the researchers. This study assesses different kinds of IDS and inclines preemptive procedures. An Intrusion Detection System (IDS is used to automate the intrusion detection process. An Intrusion Deterrence System (IPS is software which has complete competencies of an intrusion detection system and it can endeavor to stop probable events.

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

    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.

  2. A Frame of Intrusion Detection Learning System Utilizing Radial Basis Function

    S.Selvakani Kandeeban

    2012-02-01

    Full Text Available The process of monitoring the events that occur in a computer system or network and analyzing them for signs of intrusion is known as Intrusion Detection System (IDS. Detection ability of most of the IDS are limited to known attack patterns; hence new signatures for novel attacks can be troublesome, time consuming and has high false alarm rate. To achieve this, system was trained and tested with known and unknown patterns with the help of Radial Basis Functions (RBF. KDD 99 IDE (Knowledge Discovery in Databases Intrusion Detection Evaluation data set was used for training and testing. The IDS is supposed to distinguish normal traffic from intrusions and to classify them into four classes: DoS, probe, R2L and U2R. The dataset is quite unbalanced, with 79% of the traffic belonging to the DoS category, 19% is normal traffic and less than 2% constitute the other three categories. The usefulness of the data set used for experimental evaluation has been demonstrated. The different metrics available for the evaluation of IDS were also introduced. Experimental evaluations were shown that the proposed methods were having the capacity of detecting a significant percentage ofrate and new attacks.

  3. The Mobile Intrusion Detection and Assessment System (MIDAS)

    Arlowe, H.D.; Coleman, D.E.

    1990-01-01

    This paper describes MIDAS, the Mobile Intrusion Detection and Assessment System. MIDAS is a security system that can be quickly deployed to provide wide area coverage for a mobile asset. MIDAS uses two passive infrared imaging sensors, one for intruder detection and one for assessment. Detected targets are tracked while assessment cameras are directed to view the intruder location for operator observation and assessment. The dual sensor design allows simultaneous detection, assessment, and tracking. Control and status information is provided to an operator using a color graphics terminal, touch panel driven menus, and a joystick for control of the assessment sensor pan and tilt. 1 ref., 5 figs.

  4. A Comprehensive Study on Classification of Passive Intrusion and Extrusion Detection System

    A.Kalaivani

    2013-05-01

    Full Text Available Cyber criminals compromise Integrity, Availability and Confidentiality of network resources in cyber space and cause remote class intrusions such as U2R, R2L, DoS and probe/scan system attacks .To handle these intrusions, Cyber Security uses three audit and monitoring systems namely Intrusion Prevention Systems (IPS, Intrusion Detection Systems (IDS. Intrusion Detection System (IDS monitors only inbound traffic which is insufficient to prevent botnet systems. A system to monitor outbound traffic is named as Extrusion Detection System (EDS. Therefore a hybrid system should be designed to handle both inbound and outbound traffic. Due to the increased false alarms preventive systems do not suite to an organizational network. The goal of this paper is to devise a taxonomy for cyber security and study the existing methods of Intrusion and Extrusion Detection systems based on three primary characteristics. The metrics used to evaluate IDS and EDS are also presented.

  5. MIDAS, the Mobile Intrusion Detection and Assessment System

    Arlowe, H.D.; Coleman, D.E.; Williams, J.D.

    1990-01-01

    MIDAS is a semiautomated passive detection and assessment security system that can be quickly deployed to provide wide-area coverage for a mobile military asset. Designed to be mounted on top of an unguyed telescoping mast, its specially packaged set of 32 infrared sensors spin 360 degrees every two seconds. The unit produces a low resolution infrared image by sampling each sensor more than 16,000 times in a single 360-degree rotation. Drawing from image processing techniques, MIDAS detects vehicular and pedestrian intruders and produces an alarm when an intrusion is detected. Multiple intruders are tracked. MIDAS automatically directs either an assessment camera or a FLIR to one of the tracks. The alerted operator assesses the intruder and initiates a response. Once the operator assesses an intruder, the system continues to track it without generating new alarms. Because the system will track multiple targets and because the assessment system is a separate pan and tilt unit, the detection and tracking system cannot be blind-sided while the operator is assessing a diversionary intrusion. 4 figs.

  6. Cross-layer design for intrusion detection and data security in wireless ad hoc sensor networks

    Hortos, William S.

    2007-09-01

    and trust neighborhood, collecting parametric information and executing assigned decision tasks. The communications overhead due to security mechanisms and the latency in network response are thus minimized by reducing the need to move large amounts of audit data through resource-limited nodes and by locating detection/identification programs closer to audit data. If network partitioning occurs due to uncoordinated node exhaustion, data compromise or other effects of the attacks, the mobile agents can continue to operate, thereby increasing fault tolerance in the network response to intrusions. Since the mobile agents behave like an ant colony in securing the WSN, published ant colony optimization (ACO) routines and other evolutionary algorithms are adapted to protect network security, using data at and through nodes to create audit records to detect and respond to denial-of-service attacks. Performance evaluations of algorithms are performed by simulation of a few intrusion attacks, such as black hole, flooding, Sybil and others, to validate the ability of the cross-layer algorithms to enable WSNs to survive the attacks. Results are compared for the different algorithms.

  7. Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection.

    Al-Jarrah, Omar Y; Alhussein, Omar; Yoo, Paul D; Muhaidat, Sami; Taha, Kamal; Kim, Kwangjo

    2016-08-01

    Botnets, which consist of remotely controlled compromised machines called bots, provide a distributed platform for several threats against cyber world entities and enterprises. Intrusion detection system (IDS) provides an efficient countermeasure against botnets. It continually monitors and analyzes network traffic for potential vulnerabilities and possible existence of active attacks. A payload-inspection-based IDS (PI-IDS) identifies active intrusion attempts by inspecting transmission control protocol and user datagram protocol packet's payload and comparing it with previously seen attacks signatures. However, the PI-IDS abilities to detect intrusions might be incapacitated by packet encryption. Traffic-based IDS (T-IDS) alleviates the shortcomings of PI-IDS, as it does not inspect packet payload; however, it analyzes packet header to identify intrusions. As the network's traffic grows rapidly, not only the detection-rate is critical, but also the efficiency and the scalability of IDS become more significant. In this paper, we propose a state-of-the-art T-IDS built on a novel randomized data partitioned learning model (RDPLM), relying on a compact network feature set and feature selection techniques, simplified subspacing and a multiple randomized meta-learning technique. The proposed model has achieved 99.984% accuracy and 21.38 s training time on a well-known benchmark botnet dataset. Experiment results demonstrate that the proposed methodology outperforms other well-known machine-learning models used in the same detection task, namely, sequential minimal optimization, deep neural network, C4.5, reduced error pruning tree, and randomTree. PMID:26540724

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

    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. Nuclear-power-plant perimeter-intrusion alarm systems

    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.

  10. Immune System Approaches to Intrusion Detection - A Review

    Kim, Jungwon; Aickelin, Uwe; Greensmith, Julie; Tedesco, Gianni; Twycross, Jamie

    2008-01-01

    The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we review the algorithms used, the development of the systems and the outcome of their implementation. We provide an introduction and analysis of the key developments within this field, in addition to making suggestions for future research.

  11. Intrusion Detection System with Hierarchical Different Parallel Classification

    Behrouz Safaiezadeh

    2015-12-01

    Full Text Available Todays, lives integrated to networks and internet. The needed information is transmitted through networks. So, someone may attempt to abuse the information and attack and make changes by weakness of networks. Intrusion Detection System is a system capable to detect some attacks. The system detects attacks through classifier construction and considering IP in network. The recent researches showed that a fundamental classification cannot be effective lonely and due to its errors, but mixing some classifications provide better efficiency. So, the current study attempt to design three classes of support vector machine, the neural network of multilayer perceptron and parallel fuzzy system in which there are trained dataset and capability to detect two classes. Finally, decisions made by an intermediate network due to type of attack. In the present research, suggested system tested through dataset of KDD99 and results indicated appropriate efficiency 99.71% in average.

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

    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.

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

    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.

  14. Fracture density estimation from petrophysical log data using the adaptive neuro-fuzzy inference system

    Fractures as the most common and important geological features have a significant share in reservoir fluid flow. Therefore, fracture detection is one of the important steps in fractured reservoir characterization. Different tools and methods are introduced for fracture detection from which formation image logs are considered as the common and effective tools. Due to the economical considerations, image logs are available for a limited number of wells in a hydrocarbon field. In this paper, we suggest a model to estimate fracture density from the conventional well logs using an adaptive neuro-fuzzy inference system. Image logs from two wells of the Asmari formation in one of the SW Iranian oil fields are used to verify the results of the model. Statistical data analysis indicates good correlation between fracture density and well log data including sonic, deep resistivity, neutron porosity and bulk density. The results of this study show that there is good agreement (correlation coefficient of 98%) between the measured and neuro-fuzzy estimated fracture density

  15. An Intrusion Detection System for Kaminsky DNS Cache poisoning

    Dhrubajyoti Pathak, Kaushik Baruah

    2013-09-01

    Full Text Available Domain Name System (DNS is the largest and most actively distributed, hierarchical and scalable database system which plays an incredibly inevitable role behind the functioning of the Internet as we know it today. A DNS translates human readable and meaningful domain names such as www.iitg.ernet.in into an Internet Protocol (IP address such as 202.141.80.6. It is used for locating a resource on the World Wide Web. Without a DNS, the Internet services as we know it, would come to a halt. In our thesis, we proposed an Intrusion Detection System(IDS for Kaminsky cache poisoning attacks. Our system relies on the existing properties of the DNS protocol.

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

    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.

  17. RESEARCH ON SECURITY PROTOCOL FOR COLLABORATING MOBILE AGENTS IN NETWORK INTRUSION DETECTION SYSTEMS

    Olumide Simeon Ogunnusi

    2013-01-01

    Full Text Available Despite the popularity of mobile agents in academic and commercial arena, the security issues associated with them have hindered their adoption on large scale distributed applications. However, researchers are making relentless effort to overcome the security impediments so that the interesting properties inherent in mobile agent application, especially in the field of intrusion detection, can be harnessed. Such properties include: adaptability, autonomous nature, low bandwidth utilization, latency eradication, mobility and intelligence. A number of protocols have been developed by researchers for different key distribution techniques to enhance their performance and to protect communicating entities against malicious attacks that can hinder their activities. However, they do not take into account the availability and fault tolerance of the protocols in case of any possible attack despite the authentication methods offered by encryption. This study therefore, proposes a fault-tolerant key distribution protocol for distributed mobile agents (communicating entities in network intrusion detection system to facilitate hitch-free collaboration geared towards intrusive packets detection in Wireless Local Area Network (WLAN.

  18. Intrusion detection system and technology of layered wireless sensor network based on Agent

    Genjian Yu; Kunpeng Weng

    2013-01-01

    The intrusion detection system and technology of classified layered-wireless sensor network was able to meet the high safety requirements of wireless sensor network, it is urgent for us to improve the identification and generalization of detection system about characters of intrusion. In this paper, we design an intelligent intrusion detection system which realize intelligence, the effective and direct way was to add the methods,  and it was used for identification and generalization of intru...

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

    S. Devaraju; Ramakrishnan, S.

    2014-01-01

    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 cla...

  20. A Scalable Intrusion Detection System for IPv6

    LIU Bin; LI Zhitang; LI Zhanchun

    2006-01-01

    The next generation protocol IPv6 brings the new challenges to the information security. This paper presents the design and implementation of a network-based intrusion detection system that support both IPv6 protocol and IPv4 protocol. This system's architecture is focused on performance, simplicity, and scalability. There are four primary subsystems that make it up: the packet capture, the packet decoder, the detection engine, and the logging and alerting subsystem. This paper further describes a new approach to packet capture whose goal is to improve the performance of the capture process at high speeds. The evaluation shows that the system has a good performance to detect IPv6 attacks and IPv4 attacks, and achieves 61% correct detection rate with 20% false detection rate at the speed of 100 Mb·s-1.

  1. Analysis of Fuzzy Logic Based Intrusion Detection Systems in Mobile Ad Hoc Networks

    A. Chaudhary

    2014-01-01

    Full Text Available Due to the advancement in wireless technologies, many of new paradigms have opened for communications. Among these technologies, mobile ad hoc networks play a prominent role for providing communication in many areas because of its independent nature of predefined infrastructure. But in terms of security, these networks are more vulnerable than the conventional networks because firewall and gateway based security mechanisms cannot be applied on it. That’s why intrusion detection systems are used as keystone in these networks. Many number of intrusion detection systems have been discovered to handle the uncertain activity in mobile ad hoc networks. This paper emphasized on proposed fuzzy based intrusion detection systems in mobile ad hoc networks and presented their effectiveness to identify the intrusions. This paper also examines the drawbacks of fuzzy based intrusion detection systems and discussed the future directions in the field of intrusion detection for mobile ad hoc networks.

  2. A Study of Various Intrusion Detection Model Based on Data Fusion, Neural Network and D-S Theory

    Ramnaresh Sharma

    2012-06-01

    Full Text Available Network security and awareness of network attack are hot pots in current research area. Now in days various model and method are available for intrusion detection and awareness of cyber-attack. Such as Application of the integrated Network Security Situation Awareness system (Net-SSA shows that the proposed framework supports for the accurate modeling and effective generation of network security situation. In this paper we have discuss various approach for intrusion detection technique such as data fusion, neural network and D-S Theory and fuzzy logic.

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

    Coffland, Douglas R.

    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.

  4. Energy Efficient Cluster-Based Intrusion Detection System for Wireless Sensor Networks

    Manal Abdullah

    2014-09-01

    Full Text Available Wireless sensor networks (WSNs are network type where sensors are used to collect physical measurements. It has many application areas such as healthcare, weather monitoring and even military applications. Security in this kind of networks is a big concern especially in the applications that required confidentiality and privacy. Therefore, providing a WSN with an intrusion detection system is essential to protect its security from different types of intrusions, cyber-attacks and random faults. Clustering has proven its efficiency in prolong the node as well as the whole WSN lifetime. In this paper we have designed an Intrusion Detection (ID system based on Stable Election Protocol (SEP for clustered heterogeneous WSNs. The benefit of using SEP is that it is a heterogeneous-aware protocol to prolong the time interval before the death of the first node. KDD Cup’99 data set is used as the training data and test data. After normalizing our dataset, we trained the system to detect four types of attacks which are Probe, Dos, U2R and R2L, using 18 features out of the 42 features available in KDD Cup'99 dataset. The research used the K-nearest neighbour (KNN classifier for anomaly detection. The experiments determine K = 5 for best classification and this reveals recognition rate of attacks as 75%. Results are compared with KNN classifier for anomaly detection without using a clustering algorithm.

  5. Intrusion detection system and technology of layered wireless sensor network based on Agent

    Genjian Yu

    2013-08-01

    Full Text Available The intrusion detection system and technology of classified layered-wireless sensor network was able to meet the high safety requirements of wireless sensor network, it is urgent for us to improve the identification and generalization of detection system about characters of intrusion. In this paper, we design an intelligent intrusion detection system which realize intelligence, the effective and direct way was to add the methods,  and it was used for identification and generalization of intrusion characters to the Agent function of intrusion detection. It could obtain credible judgment by updating and examining the database for the actions which the general misuse detection or anomaly detection were not sure if the intrusion was formed.

  6. Adaptive shared control system

    Sanders, David

    2009-01-01

    A control system to aid mobility is presented that is intended to assist living independently and that provides physical guidance. The system has two levels: a human machine interface and an adaptive shared controller.

  7. HIERARCHICAL DESIGN BASED INTRUSION DETECTION SYSTEM FOR WIRELESS AD HOC SENSOR NETWORK

    Mohammad Saiful Islam Mamun

    2010-07-01

    Full Text Available In recent years, wireless ad hoc sensor network becomes popular both in civil and military jobs.However, security is one of the significant challenges for sensor network because of their deploymentin open and unprotected environment. As cryptographic mechanism is not enough to protect sensornetwork from external attacks, intrusion detection system needs to be introduced. Though intrusionprevention mechanism is one of the major and efficient methods against attacks, but there might besome attacks for which prevention method is not known. Besides preventing the system from someknown attacks, intrusion detection system gather necessary information related to attack technique andhelp in the development of intrusion prevention system. In addition to reviewing the present attacksavailable in wireless sensor network this paper examines the current efforts to intrusion detectionsystem against wireless sensor network. In this paper we propose a hierarchical architectural designbased intrusion detection system that fits the current demands and restrictions of wireless ad hocsensor network. In this proposed intrusion detection system architecture we followed clusteringmechanism to build a four level hierarchical network which enhances network scalability to largegeographical area and use both anomaly and misuse detection techniques for intrusion detection. Weintroduce policy based detection mechanism as well as intrusion response together with GSM cellconcept for intrusion detection architecture.

  8. A model for anomaly classification in intrusion detection systems

    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.

  9. A Frequency-Based Approach to Intrusion Detection

    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. Evaluating the Strengths and Weaknesses of Mining Audit Data for Automated Models for Intrusion Detection in Tcpdump and Basic Security Module Data

    A. Arul Lawrence Selvakumar; G. Mohammed Nazer

    2012-01-01

    Problem statement: Intrusion Detection System (IDS) have become an important component of infrastructure protection mechanism to secure the current and emerging networks, its services and applications by detecting, alerting and taking necessary actions against the malicious activities. The network size, technology diversities and security policies make networks more challenging and hence there is a requirement for IDS which should be very accurate, adaptive, extensible and more reliable. Alth...

  11. A Neuro-genetic Based Short-term Forecasting Framework for Network Intrusion Prediction System

    Siva S. Sivatha Sindhu; S. Geetha; M. Marikannan; A. Kannan

    2009-01-01

    Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by "authorized" users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system (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 IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference (KDD 2009) intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS (NGIDS) involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this

  12. Design And Efficient Deployment Of Honeypot And Dynamic Rule Based Live Network Intrusion Collaborative System

    Renuka Prasad.B

    2011-03-01

    Full Text Available The continuously emerging, operationally and managerially independent, geographically distributedcomputer networks deployable in an evolutionarily manner have created greater challenges in securingthem. Several research works and experiments have convinced the security expert that Network IntrusionDetection Systems (NIDS or Network Intrusion Prevention Systems (NIPS alone are not capable ofsecuring the Computer Networks from internal and external threats completely. In this paper we presentthe design of Intrusion Collaborative System which is a combination of NIDS,NIPS, Honeypots, softwaretools like nmap, iptables etc. Our Design is tested against existing attacks based on Snort Rules andseveral customized DDOS , remote and guest attacks. Dynamic rules are generated during every unusualbehavior that helps Intrusion Collaborative System to continuously learn about new attacks. Also aformal approach to deploy Live Intrusion Collaboration Systems based on System of Systems Concept isProposed.

  13. Intrusion Detection Systems and Intrusion Prevention System with Snort provided by Security Onion.

    Bezborodov, Sergey

    2016-01-01

    In this thesis I wanted to get familiar with Snort IDS/IPS. I used the Security Onion distribution with a lot of security tools, but I concentrated on Snort. Also I needed to evaluate Security Onion environment and check what features it provides for processing with Snort. During the work I needed to figure out the pros and cons of using Security Onion with Snort as a security system for network. I compared it with alternatives and briefly describe it. As result I installed Security Onion,...

  14. Methods and algorithms of selection the informative attributes in systems of adaptive data processing for analysis and forecasting

    Olimjan Djumanov

    2012-01-01

    The principles, methods and algorithms of informative attributes selection were developed for optimization of description and representation for the objects in systems of adaptive data processing, where data are non-stationary by nature. The proposed algorithms of informative attributes selection for one-dimensional time series are based on the simplified ratings of correlation, mathematical expectation, dispersion of attributes. The algorithms have been developed using dynamic properties of ...

  15. An Agent-Based Intrusion Detection System for Local Area Networks

    Sen, Jaydip

    2010-01-01

    Since it is impossible to predict and identify all the vulnerabilities of a network beforehand, and penetration into a system by malicious intruders cannot always be prevented, intrusion detection systems (IDSs) are essential entities to ensure the security of a networked system. To be effective in carrying out their functions, the IDSs need to be accurate, adaptive, and extensible. Given these stringent requirements and the high level of vulnerabilities of the current days’ networks, the design of an IDS has become a very challenging task. Although, an extensive research has been done on intrusion detection in a distributed environment, distributed IDSs suffer from a number of drawbacks e.g., high rates of false positives, low detection efficiency etc. In this paper, the design of a distributed IDS is proposed that consists of a group of autonomous and cooperating agents. In addition to its ability to detect attacks, the system is capable of identifying and isolating compromised nodes in the network the...

  16. Novel Model for Intrusion Detection

    Li Jia-chun; Li Zhi-tang

    2003-01-01

    It's very difficult that the traditional intrusion detection methods based on accurate match adapt to the blur and uncertainty of user information and expert knowledge, it results in failing to report the variations of attack signature. In addition security itself includes fuzziness, the judgment standard of confidentiality, integrity and availability of system resource is uncertain. In this paper fuzzy intrusion detection based on partial match is presented to detect some types of attacks availably and alleviate some of the difficulties of above approaches, the architecture of fuzzy intrusion detection system(FIDS) is introduced and its performance is analyzed.

  17. Novel Model for Intrusion Detection

    Li; Jia-chun; Li; Zhi-tang

    2003-01-01

    It's very difficult that the traditional intrusion detection methods based on accurate match adapt to the blur and uncertainty of user information and expert knowledge, it results in failing to report the variation of attack signature.In addition security itself includes fuzziness, the judgment standard of confidentiality, integrity and availability of system resource is uncertain. In this paper fuzzy intrusion detection based on partial match is presented to detect some types of attacks availably and alleviate some of the difficulties of above approaches, the architecture of fuzzy intrusion detection system(FIDS) is introduced and its performance is analyzed.

  18. Fast and Adaptive Lossless On-Board Hyperspectral Data Compression System for Space Applications

    Aranki, Nazeeh; Bakhshi, Alireza; Keymeulen, Didier; Klimesh, Matthew

    2009-01-01

    Efficient on-board lossless hyperspectral data compression reduces the data volume necessary to meet NASA and DoD limited downlink capabilities. The techniques also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware, which makes it practical for flight implementations of pushbroom instruments. A prototype of the compressor (and decompressor) of the algorithm is available in software, but this implementation may not meet speed and real-time requirements of some space applications. Hardware acceleration provides performance improvements of 10x-100x vs. the software implementation (about 1M samples/sec on a Pentium IV machine). This paper describes a hardware implementation of the JPL-developed 'Fast Lossless' compression algorithm on a Field Programmable Gate Array (FPGA). The FPGA implementation targets the current state of the art FPGAs (Xilinx Virtex IV and V families) and compresses one sample every clock cycle to provide a fast and practical real-time solution for Space applications.

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

    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.

  20. An immunity-based model for dynamic distributed intrusion detection

    Qiao, Peili; Wang, Tong; Su, Jie

    2008-03-01

    The traditional intrusion detection systems mostly adopt the analysis engine of the concentrating type, so the misinformation rate is higher and lack of self-adaptability, which is already difficult to meet increasing extensive security demand of the distributed network environment. An immunity-based model combining immune theory, data mining and data fusion technique for dynamic distributed intrusion detection is proposed in this paper. This system presents the method of establishing and evolving the set of early gene, and defines the sets of Self, Nonself and Immunity cells. Moreover, a detailed description is given to the architecture and work mechanism of the model, and the characters of the model are analyzed.

  1. Intrusion Detection System using Self Organizing Map: A Survey

    Kruti Choksi

    2014-12-01

    Full Text Available Due to usage of computer every field, Network Security is the major concerned in today’s scenario. Every year the number of users and speed of network is increasing, along with it online fraud or security threats are also increasing. Every day a new attack is generated to harm the system or network. It is necessary to protect the system or networks from various threats by using Intrusion Detection System which can detect “known” as well as “unknown” attack and generate alerts if any unusual behavior in the traffic. There are various approaches for IDS, but in this paper, survey is focused on IDS using Self Organizing Map. SOM is unsupervised, fast conversion and automatic clustering algorithm which is able to handle novelty detection. The main objective of the survey is to find and address the current challenges of SOM. Our survey shows that the existing IDS based on SOM have poor detection rate for U2R and R2L attacks. To improve it, proper normalization technique should be used. During the survey we also found that HSOM and GHSOM are advance model of SOM which have their own unique feature for better performance of IDS. GHSOM is efficient due to its low computation time. This survey is beneficial to design and develop efficient SOM based IDS having less computation time and better detection rate.

  2. HYBRID ARCHITECTURE FOR DISTRIBUTED INTRUSION DETECTION SYSTEM IN WIRELESS NETWORK

    Seyedeh Yasaman Rashida

    2013-01-01

    In order to the rapid growth of the network application, new kinds of network attacks are emerging endlessly. So it is critical to protect the networks from attackers and the Intrusion detection technology becomes popular. Therefore, it is necessary that this security concern must be articulate right from the beginning of the network design and deployment. The intrusion detection technology is the process of identifying network activity that can lead to a compromise of security po...

  3. Necessity to adapt land use and land cover classification systems to readily accept radar data

    Drake, B.

    1977-01-01

    A hierarchial, four level, standardized system for classifying land use/land cover primarily from remote-sensor data (USGS system) is described. The USGS system was developed for nonmicrowave imaging sensors such as camera systems and line scanners. The USGS system is not compatible with the land use/land cover classifications at different levels that can be made from radar imagery, and particularly from synthetic-aperture radar (SAR) imagery. The use of radar imagery for classifying land use/land cover at different levels is discussed, and a possible revision of the USGS system to more readily accept land use/land cover classifications from radar imagery is proposed.

  4. Securing Wireless Sensor Network (WSN Using Embedded Intrusion Detection Systems

    Qutaiba I. Ali

    2012-06-01

    Full Text Available This paper focuses on designing distributed wireless sensor network gateways armed with Intrusion Detection System (IDS. The main contribution of this work is the attempt to insert IDS functionality into the gateway node (UBICOM IP2022 network processor chip itself. This was achieved by building a light weight signature based IDS based on the famous open source SNORT IDS. Regarding gateway nodes, as they have limited processing and energy constrains, the addition of further tasks (the IDS program may affects seriously on its performance, so that, the current design takes these constrains into consideration as a priority and use a special protocol to achieve this goal. In order to optimize the performance of the gateway nodes, some of the preprocessing tasks were offloaded from the gateway nodes to a suggested classification and processing server and a new searching algorithm was suggested. Different measures were taken to validate the design procedure and a detailed simulation model was built to discover the behavior of the system in different environments.

  5. Adaptable Embedded Systems

    Lisbôa, Carlos; Carro, Luigi

    2013-01-01

    As embedded systems become more complex, designers face a number of challenges at different levels: they need to boost performance, while keeping energy consumption as low as possible, they need to reuse existent software code, and at the same time they need to take advantage of the extra logic available in the chip, represented by multiple processors working together.  This book describes several strategies to achieve such different and interrelated goals, by the use of adaptability. Coverage includes reconfigurable systems, dynamic optimization techniques such as binary translation and trace reuse, new memory architectures including homogeneous and heterogeneous multiprocessor systems, communication issues and NOCs, fault tolerance against fabrication defects and soft errors, and finally, how one can combine several of these techniques together to achieve higher levels of performance and adaptability.  The discussion also includes how to employ specialized software to improve this new adaptive system, and...

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

    Herckenrath, Daan; Odlum, Nick; Nenna, Vanessa;

    2013-01-01

    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 be...... obtained to provide high-resolution three-dimensional models of subsurface resistivity variations that can be related to geology and salt concentrations on a regional scale. Several previous studies have calibrated salt water intrusion models with geophysical data, but are typically limited to the use of...... errors, we perform a coupled hydrogeophysical inversion (CHI) in which we use a salt water intrusion model to interpret the geophysical data and guide the geophysical inversion. We refer to this methodology as a Coupled Hydrogeophysical Inversion-State (CHI-S), in which simulated salt concentrations are...

  7. A Behavior Based Intrusion Detection System Using Machine Learning Algorithms

    Murat OĞUZ

    2016-06-01

    Full Text Available Humans are consistently referred to as the weakest link in information security. Human factors such as individual differences, cognitive abilities and personality traits can impact on behavior and play a significant role in information security. The purpose of this study is to identify, describe and classify the human factors affecting Information Security and develop a model to reduce the risk of insider misuse and assess the use and performance of the best-suited artificial intelligence techniques in detection of misuse. More specifically, this study provides a comprehensive view of the human related information security risks and threats, classification study of the human related threats in information security, a methodology developed to reduce the risk of human related threats by detecting insider misuse by a behavior-based intrusion detection system using machine learning algorithms, and the comparison of the numerical experiments for analysis of this approach. Specifically, by using the machine learning algorithm with the best learning performance, the detection rates of the attack types defined in the organized five dimensional human threats taxonomy were determined. Lastly, the possible human factors affecting information security as linked to the detection rates were sorted upon the evaluation of the taxonomy.

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

    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.

  9. Experimental Study of Nuclear Security System Components for Achieving the Intrusion Process via Sensor's Network System

    Cluster sensors are one of nuclear security system components which are used to detect any intrusion process of the nuclear sites. In this work, an experimental measuring test for sensor performance and procedures are presented. Sensor performance testing performed to determine whether a particular sensor will be acceptable in a proposed design. We have access to a sensors test field in which the sensor of interest is already properly installed and the parameters have been set to optimal levels by preliminary testing. The glass-breakage (G.B) and open door (O.D) sensors construction, operation and design for the investigated nuclear site are explained. Intrusion tests were carried out inside the field areas of the sensors to evaluate the sensor performance during the intrusion process. Experimental trials were performed for achieving the intrusion process via sensor network system. The performance and intrusion senses of cluster sensors inside the internal zones was recorded and evaluated. The obtained results explained that the tested and experimented G.B sensors have a probability of detection P (D) value 65% founded, and 80% P (D) of Open-door sensor

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

    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

  11. Design and implementation of self-protection agent for network-based intrusion detection system

    朱树人; 李伟琴

    2003-01-01

    Static secure techniques, such as firewall, hierarchy filtering, distributed disposing,layer management, autonomy agent, secure communication, were introduced in distributed intrusion detection. The self-protection agents were designed, which have the distributed architecture,cooperate with the agents in intrusion detection in a loose-coupled manner, protect the security of intrusion detection system, and respond to the intrusion actively. A prototype self-protection agent was implemented by using the packet filter in operation system kernel. The results show that all the hosts with the part of network-based intrusion detection system and the whole intrusion detection system are invisible from the outside and network scanning, and cannot apperceive the existence of network-based intrusion detection system. The communication between every part is secure. In the low layer, the packet streams are controlled to avoid the buffer leaks exist ing in some system service process and back-door programs, so as to prevent users from misusing and vicious attack like Trojan Horse effectively.

  12. 基于数字属性和符号属性混合数据的网络异常入侵检测方法%Network-based anomaly intrusion detection with numeric-and-nominal mixed data

    蔡龙征; 余胜生; 王晓峰; 周敬利

    2006-01-01

    Anomaly detection is a key element of intrusion detection systems and a necessary complement of widely used misuse intrusion detection systems. Data sources used by network intrusion detection, like network packets or connections, often contain both numeric and nominal features. Both of these features contain important information for intrusion detection. These two features, on the other hand, have different characteristics. This paper presents a new network based anomaly intrusion detection approach that works well by building profiles for numeric and nominal features in different ways. During training, for each numeric feature, a normal profile is build through statistical distribution inference and parameter estimation, while for each nominal feature, a normal profile is setup through statistical method. These profiles are used as detection models during testing to judge whether a data being tested is benign or malicious. Experiments with the data set of 1999 DARPA (defense advanced research project agency) intrusion detection evaluation show that this approach can detect attacks effectively.

  13. Applying an Ontology to a Patrol Intrusion Detection System for Wireless Sensor Networks

    Chia-Fen Hsieh; Rung-Ching Chen; Yung-Fa Huang

    2014-01-01

    With the increasing application of wireless sensor networks (WSN), the security requirements for wireless sensor network communications have become critical. However, the detection mechanisms of such systems impact the effectiveness of the entire network. In this paper, we propose a lightweight ontology-based wireless intrusion detection system (OWIDS). The system applies an ontology to a patrol intrusion detection system (PIDS). A PIDS is used to detect anomalies via detection knowledge. The...

  14. STUDYING COMPLEX ADAPTIVE SYSTEMS

    John H. Holland

    2006-01-01

    Complex adaptive systems (cas) - systems that involve many components that adapt or learn as they interact - are at the heart of important contemporary problems. The study of cas poses unique challenges: Some of our most powerful mathematical tools, particularly methods involving fixed points, attractors, and the like, are of limited help in understanding the development of cas. This paper suggests ways to modify research methods and tools, with an emphasis on the role of computer-based models, to increase our understanding of cas.

  15. Improving Bee Algorithm Based Feature Selection in Intrusion Detection System Using Membrane Computing

    Kazeem I. Rufai

    2014-03-01

    Full Text Available Despite the great benefits accruable from the debut of computer and the internet, efforts are constantly being put up by fraudulent and mischievous individuals to compromise the integrity, confidentiality or availability of electronic information systems. In Cyber-security parlance, this is termed ‘intrusion’. Hence, this has necessitated the introduction of Intrusion Detection Systems (IDS to help detect and curb different types of attack. However, based on the high volume of data traffic involved in a network system, effects of redundant and irrelevant data should be minimized if a qualitative intrusion detection mechanism is genuinely desirous. Several attempts, especially feature subset selection approach using Bee Algorithm (BA, Linear Genetic Programming (LGP, Support Vector Decision Function Ranking (SVDF, Rough, Rough-DPSO, and Mutivariate Regression Splines (MARS have been advanced in the past to measure the dependability and quality of a typical IDS. The observed problem among these approaches has to do with their general performance. This has therefore motivated this research work. We hereby propose a new but robust algorithm called membrane algorithm to improve the Bee Algorithm based feature subset selection technique. This Membrane computing paradigm is a class of parallel computing devices. Data used were taken from KDD-Cup 99 Dataset which is the acceptable standard benchmark for intrusion detection. When the final results were compared to those of the existing approaches, using the three standard IDS measurements-Attack Detection, False Alarm and Classification Accuracy Rates, it was discovered that Bee Algorithm-Membrane Computing (BA-MC approach is a better technique. This is because our approach produced very high attack detection rate of 89.11%, classification accuracy of 95.60% and also generated a reasonable decrease in false alarm rate of 0.004. Receiver Operating Characteristic (ROC curve was used for results

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

    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.

  17. Adaptive Inflow Control System

    Volkov, Vasily Y; Zhuravlev, Oleg N; Nukhaev, Marat T; Shchelushkin, Roman V

    2014-01-01

    This article presents the idea and realization for the unique Adaptive Inflow Control System being a part of well completion, able to adjust to the changing in time production conditions. This system allows to limit the flow rate from each interval at a certain level, which solves the problem of water and gas breakthroughs. We present the results of laboratory tests and numerical calculations obtaining the characteristics of the experimental setup with dual-in-position valves as parts of adaptive inflow control system, depending on the operating conditions. The flow distribution in the system was also studied with the help of three-dimensional computer model. The control ranges dependences are determined, an influence of the individual elements on the entire system is revealed.

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

    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...

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

    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...

  20. A Recent Survey on Bloom Filters in Network Intrusion Detection Systems

    K.Saravanan,

    2011-03-01

    Full Text Available Computer networks are prone to hacking, viruses and other malware; a Network Intrusion Detection System (NIDS is needed to protect the end-user machines from threats. An effective NIDS is therefore anetwork security system capable of protecting the end user machines well before a threat or intruder affects. NIDS requires a space efficient data base for detection of threats in high speed conditions. A bloom filter is a space efficient randomized data structure for representing a set in order to support membership queries. These Bloom filters allow false positive results (FPR but the space saving capability often outweigh this drawback provided the probability of FPR is controlled. Research is being done to reduce FPR by modifying the structure of bloom filters and enabling it to operate in the increasing network speeds, thus variant bloom filters are being introduced. The aim of this paper is to survey the ways in which Bloom filters have been used and modified to be used in high speed Network Intrusion Detection Systems with their merits and demerits.

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

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

    2015-01-01

    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. PMID:26593915

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

    Ismail Butun; In-Ho Ra; Ravi Sankar

    2015-01-01

    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...

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

    Gonzalez, J. [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Ruiz, M., E-mail: mariano.ruiz@upm.e [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Barrera, E.; Lopez, J.M.; Arcas, G. de [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain)

    2010-07-15

    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.

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

    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.

  5. Services oriented architecture for adaptive and intelligent data acquisition and processing systems in long pulse fusion experiments

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

  6. Bald Mountain gold mining district, Nevada: A Jurassic reduced intrusion-related gold system

    Nutt, C.J.; Hofstra, A.H.

    2007-01-01

    The Bald Mountain mining district has produced about 2 million ounces (Moz) of An. Geologic mapping, field relationships, geochemical data, petrographic observations, fluid inclusion characteristics, and Pb, S, O, and H isotope data indicate that An mineralization was associated with a reduced Jurassic intrusion. Gold deposits are localized within and surrounding a Jurassic (159 Ma) quartz monzonite porphyry pluton and dike complex that intrudes Cambrian to Mississippian carbonate and clastic rocks. The pluton, associated dikes, and An mineralization were controlled by a crustal-scale northwest-trending structure named the Bida trend. Gold deposits are localized by fracture networks in the pluton and the contact metamorphic aureole, dike margins, high-angle faults, and certain strata or shale-limestone contacts in sedimentary rocks. Gold mineralization was accompanied by silicification and phyllic alteration, ??argillic alteration at shallow levels. Although An is typically present throughout, the system exhibits a classic concentric geochemical zonation pattern with Mo, W, Bi, and Cu near the center, Ag, Pb, and Zn at intermediate distances, and As and Sb peripheral to the intrusion. Near the center of the system, micron-sized native An occurs with base metal sulfides and sulfosalts. In peripheral deposits and in later stages of mineralization, Au is typically submicron in size and resides in pyrite or arsenopyrite. Electron microprobe and laser ablation ICP-MS analyses show that arsenopyrite, pyrite, and Bi sulfide minerals contain 10s to 1,000s of ppm Au. Ore-forming fluids were aqueous and carbonic at deep levels and episodically hypersaline at shallow levels due to boiling. The isotopic compositions of H and O in quartz and sericite and S and Pb in sulfides are indicative of magmatic ore fluids with sedimentary sulfur. Together, the evidence suggests that Au was introduced by reduced S-bearing magmatic fluids derived from a reduced intrusion. The reduced

  7. A Novel Datamining Based Approach for Remote Intrusion Detection

    Renu Deepti.S, Loshma.G

    2012-06-01

    Full Text Available Today, as information systems are more open to the Internet,attacks and intrusions are also increasing rapidly so the importance of secure networks is also vital. New intelligent Intrusion Detection Systems which are based on sophisticated algorithms are in demand.Intrusion Detection System (IDS is an important detection used as a countermeasure to preserve data integrity and system availability from attacks. It is a combination of software and hardware that attempts to perform intrusion detection.In data mining based intrusion detection system, we should make use of particular domain knowledge in relation to intrusion detection in order to efficiently extract relative rules from large amounts of records.This paper proposes boosting method for intrusion detection and it is possible to detect the intrusions in all the Systems, without installing the Software in client System (like client-server via Web service (Apache tomcat by using the ip address of the client system.

  8. Unsupervised Training Methods for Non-intrusive Appliance Load Monitoring from Smart Meter Data

    Parson, Oliver

    2014-01-01

    Non-intrusive appliance load monitoring (NIALM) is the process of disaggregating a household’s total electricity consumption into its contributing appliances. Smart meters are currently being deployed on national scales, providing a platform to collect aggregate household electricity consumption data. Existing approaches to NIALM require a manual training phase in which either sub-metered appliance data is collected or appliance usage is manually labelled. This training data is used to build ...

  9. Dataport and NILMTK: a building data set designed for non-intrusive load monitoring

    Parson, Oliver; Fisher, Grant; Hersey, April; Batra, Nipun; Kelly, Jack; Singh, Amarjeet; Knottenbelt, William; Rogers, Alex

    2015-01-01

    Non-intrusive load monitoring (NILM), or energy disaggregation, is the process of using signal processing and machine learning to separate the energy consumption of a building into individual appliances. In recent years, a number of data sets have been released in order to evaluate such approaches, which contain both building-level and appliance-level energy data. However, these data sets typically cover less than 10 households due to the financial cost of such deployments, and are not releas...

  10. Adaptive Noise Reduction System

    Ivana Ropuš

    2013-01-01

    Full Text Available Noise is an all-present environment pollutant, considered to be one of the greatest contemporary pollutants. World-wide, co-ordinated actions are conducted in order to develop systems which minimise the noise influence onto society.In this article we argue that novel approach to suppression of influence of noise is useful. Furthermore, we argue that the efficient approach is formulation of the efficient, broadly applicable, ubiquituous, adaptive noise-protection system. The approach combines the natural noise-protection form based on plants with the artificially formed coatings.Elements of the system are discussed, its formation and maintenance analysed and perspectives conjectured.

  11. Intrusion Detection Systems for Community Wireless Mesh Networks

    Makaroff, D.; Smith, Paul; Race, Nicholas J.P.; Hutchison, David

    2008-01-01

    Wireless mesh networks are being increasingly used to provide affordable network connectivity to communities where wired deployment strategies are either not possible or are prohibitively expensive. Unfortunately, computer networks (including mesh networks) are frequently being exploited by increasingly profit-driven and insidious attackers, which can affect their utility for legitimate use. In response to this, a number of countermeasures have been developed, including intrusion detection sy...

  12. Battery-Sensing Intrusion Protection System (B-SIPS)

    Buennemeyer, Timothy Keith

    2008-01-01

    This dissertation investigates using instantaneous battery current sensing techniques as a means of detecting IEEE 802.15.1 Bluetooth and 802.11b (Wi-Fi) attacks and anomalous activity on small mobile wireless devices. This research explores alternative intrusion detection methods in an effort to better understand computer networking threats. This research applies to Personal Digital Assistants (PDAs) and smart phones, operating with sensing software in wireless network environments to relay ...

  13. Algorithm for distributed agent based network intrusion detection system (INDS)

    Sokolovski, Aleksandar; Gelev, Saso

    2011-01-01

    The scope of this research paper is one of the most important aspects nowadays, the security and management of one computer network (methods and procedures to get a stable, reliable and redundant computer network) which is a key issue for any ICT Enterprise in this world of Information Age. This paper attempts to investigate the possible benefits of using the network security methods in combination with medical quarantine procedures, in order to create new algorithm for network intrusion d...

  14. Design & Implementation of Fast Modulo Multiplier Based Network Intrusion Detection System (NIDS using HDL

    Sachin Singh , Sunil Kumar Shah

    2012-06-01

    Full Text Available This paper covers the implementation of theimplementation of Network Intrusion Detection System(NIDS using International Data Encryption Algorithm(IDEA. The current era has seen an explosive growth incommunications. Applications like online banking,personal digital assistants, mobile communication,smartcards, etc. have emphasized the need for security inresource constrained environments. International DataEncryption Algorithm (IDEA cryptography serves as aperfect network intrusion detection system (NIDS toolbecause of its 128 bits key sizes and high securitycomparable to that of other algorithms. However, to matchthe ever increasing requirement for speed in today’sapplications, hardware acceleration of the cryptographicalgorithms is a necessity. This study presents an efficienthardware structure for the modulo (2n + 1 Multiplier,which is the most time and space consuming operation inIDEA. The proposed modulo multiplier saves more time,area and cost. The block size considered here is same as oftraditional IDEA encryption algorithm which is of 64 bitswith 16 bit sub-blocks.

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

    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

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

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

    2013-01-01

    In this work, a dynamic MATLAB Simulink model of a H3-350 Reformed Methanol Fuel Cell (RMFC) stand-alone battery charger produced by Serenergy is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseous...... 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...

  17. Hierarchical Design Based Intrusion Detection System For Wireless Ad hoc Network

    Mamun, Mohammad Saiful Islam; Kabir, A. F. M Sultanul

    2012-01-01

    In recent years, wireless ad hoc sensor network becomes popular both in civil and military jobs. However, security is one of the significant challenges for sensor network because of their deployment in open and unprotected environment. As cryptographic mechanism is not enough to protect sensor network from external attacks, intrusion detection system needs to be introduced. Though intrusion prevention mechanism is one of the major and efficient methods against attacks, but there might be some...

  18. Link Adaptation for Framed Multimedia Data Transmission over a DS-CDMA Communication System

    David Declercq

    2005-02-01

    Full Text Available In the context of frame-based multimedia wireless transmission, a link adaptation strategy is proposed, assuming that the source decoder may accept some remaining errors at the output of the channel decoder. Based on a target mean bit error rate for erroneous frames, a minimum bit-energy-to-equivalent-noise ratio is chosen. Under this constraint, a new link adaptation criterion is proposed: the maximization of the minimum user's information rate through dynamic spreading gain and power control, allowing to guarantee a transmission for each and every user. An analytical solution to this constrained optimization problem is proposed and its performance is studied in a Rayleigh-fading environment.

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

    Zuo Chen; Xue Li; Bing Yang; Qian Zhang

    2015-01-01

    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...

  20. 澳大利亚造山型金矿和侵入岩有关金矿系统流体包裹体资料和矿化过程的比较%Comparison of fluid inclusion data and mineralization processes for Australian orogenic gold and intrusion-related gold systems

    T.P.Memagh; E.N.Bastrakov; Khin Zaw; A.S.Wygralak; L.A.I.Wybom

    2007-01-01

    We have examined the fluid inclusion data and fluid chemistry of Australian orogenic and intrusion-related gold deposits to determine if similar mineralization processes apply to both styles of deposits. The fluid inclusion data from the Yilgarn craton, the western subprovince of the Lachlan orogen, the Tanami, Tennant Creek and Pine Creek regions, and the Telfer gold mine show that mineralization involved fluids with broadly similar major chemical components ( i. e. H2O + NsCl + CO2 ± CH4 ± N2 ). These deposits formed over a wide range of temperature-pressure conditions ( < 200 to > 500℃, < 100 ~ 400MPa ). Low salinity, CO2-bearing inclusions and low salinity aqueous inclusions occur in both systems but the main difference between these two types of deposits is that most intrusion-related gold deposits also contain at least one population of high-salinity aqueous brine. Oxygen and hydrogen isotope data for both styles of deposit usually cannot distinguish between a magmatic or metamorphic source for the ore-bearing fluids. However, sulfur and lead isotope data for the intrusion-related gold deposits generally indicate either a magmatic source or mixing between magmatic and sedimentary sources of fluid. The metamorphic geothermal gradients associated with intrusion-related gold deposits are characterized by low pressure, high temperature metamorphism and high crustal geothermal gradients of > 30/km. Where amphibole breakdown occurs in a granite source region, the spatially related deposits are more commonly associated with Cu-Au deposits rather than Au-only deposits that are associated with lower temperature granites. The dominant processes thought to cause gold precipitation in both types of deposits are fluid-rock interaction ( e. g. desulfidation) or phase separation. Consideration of the physical and chemical properties of the H2O-NaCl-CO2 system on the nature of gold precipitation mechanisms at different crustal levels infers different roles of

  1. Evaluation of Empirical Data and Modeling Studies to Support Soil Vapor Intrusion Screening Criteria for Petroleum Hydrocarbon Compounds

    This study is an evaluation of empirical data and select modeling studies of the behavior of petroleum hydrocarbon (PHC) vapors in subsurface soils and how they can affect subsurface-to-indoor air vapor intrusion (VI), henceforth referred to as petroleum vapor intrusion or “PVI” ...

  2. Secured UAV based on multi-agent systems and embedded Intrusion Detection and Prevention Systems

    K.Boukhdir

    2015-08-01

    Full Text Available Unmanned aerial vehicles, or drones, are a relatively recent area of research and in full effervescence with more and more amateur and academic projects. Initially associated to the military, these vehicles are way to be used in many other areas. In effect, demand is growing for various applications within of this type of technology. Inspection of buildings, search and rescue of missing or in distress people are some examples. This research paper highlights a lightweight intrusion detection system with the objective to secure UAVs. Our IDP(Intrusion and Prevention System uses real-time architecture, based on the multi-agent systems so it can be autonomous and distributed between the ground control station(GCS and the UAV is more suited to be embedded in low computation resources devices in general and especially UAVs

  3. From intrusive to oscillating thoughts.

    Peirce, Anne Griswold

    2007-10-01

    This paper focused on the possibility that intrusive thoughts (ITs) are a form of an evolutionary, adaptive, and complex strategy to prepare for and resolve stressful life events through schema formation. Intrusive thoughts have been studied in relation to individual conditions, such as traumatic stress disorder and obsessive-compulsive disorder. They have also been documented in the average person experiencing everyday stress. In many descriptions of thought intrusion, it is accompanied by thought suppression. Several theories have been put forth to describe ITs, although none provides a satisfactory explanation as to whether ITs are a normal process, a normal process gone astray, or a sign of pathology. There is also no consistent view of the role that thought suppression plays in the process. I propose that thought intrusion and thought suppression may be better understood by examining them together as a complex and adaptive mechanism capable of escalating in times of need. The ability of a biological mechanism to scale up in times of need is one hallmark of a complex and adaptive system. Other hallmarks of complexity, including self-similarity across scales, sensitivity to initial conditions, presence of feedback loops, and system oscillation, are also discussed in this article. Finally, I propose that thought intrusion and thought suppression are better described together as an oscillatory cycle. PMID:17904485

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

    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.

  5. Technical evaluation of rapid deployment and re-deployable intrusion detection systems (RDIDS/RIDS)

    This paper reports on ECSI-EAG International's Pulsed Infrared Perimeter Intrusion Detection System (IPID) which was originally designed for permanent pole mounted installations and tripod mounted Rapid Deployment applications for NATO military forces. Subsequently, IPID has been upgraded to meet present Rapid Deployment Intrusion Detection System (RDIDS) and Redeployable Intrusion Detection System (RIDS) requirements. Both the RDIDS and RIDS are available in self-contained, wireless, conduitless configurations. The active, pulsed infrared system is integrated with a Radio Frequency (RF) transmitter operating in the VHF and UHF frequencies and powered by a battery backup photovoltaic energy system. The enhancements offer extensive flexibility and cash savings since the RDIDS and RIDS systems can be operational in 1/20 the time of conventional installations

  6. On the applicability of fair and adaptive data dissemination in traffic information systems

    Schwartz, Ramon S.; Ohazulike, Anthony E.; Sommer, Christoph; Scholten, Hans; Dressler, Falko; Havinga, Paul

    2014-01-01

    Vehicular Ad hoc Networks (VANETs) are expected to serve as support to the development of not only safety applications but also information-rich applications that disseminate relevant data to vehicles. Due to the continuous collection, processing, and dissemination of data, one crucial requirement i

  7. ADAPTIVE CAPACITY OF STUDENTS’ CARDIOVASCULAR SYSTEM

    Arabadzhi Liliya Ivanivna

    2012-01-01

    Data about adaptive capacity of cardiovascular system of 106 students were analyzed. Using the method of R.M. Bayevskiy, current adaptive capacity of students’ organisms was estimated. The number of students with stress adaptation mechanisms significantly increased with their age (from 17 to 23 years). In our opinion, this could be explained by negative impact of urbanization, significant learning overload and lack of physical activity among the students. Dependence of the adaptive capacity...

  8. An Intrusion Detection System Model Based on Immune Principle and Performance Analysis

    CHEN Zhi-xian; WANG Ru-chuan; WANG Shao-di; SUN Zhi-xin

    2005-01-01

    The study of security in computer networks is a key issue,which is a rapidly growing area of interest because of its importance.Main network security problems are analyzed in this paper above all,which currently are confronted with network systems and existing works in intrusion detection.And then an intrusion detection system model based on Immune Principle(IPIDS)is presented.Meanwhile,it expatiates detailed implementation of the methods how to reduce the high false positive and negative alarms of the traditional Intrusion Detection System(IDS).At last a simple simulation is performed on this model just using string match algorithm as binding mechanism.The simulation results indicate that the model can detect malicious activity effectively,and consequently the security and steadiness of the whole network system are improved also.

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

    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.

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

    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.

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

    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. PMID:22412321

  12. A Study of Various Intrusion Detection Model Based on Data Fusion, Neural Network and D-S Theory

    Ramnaresh Sharma

    2012-06-01

    Full Text Available Network security and awareness of network attackare hot pots in current research area. Now in daysvarious model and method are available forintrusion detection and awareness of cyber-attack.Such as Application of the integrated NetworkSecurity Situation Awareness system (Net-SSAshows that the proposed framework supports for theaccurate modeling and effective generation ofnetwork security situation. In this paper we havediscuss various approach for intrusion detectiontechnique such as data fusion, neural network andD-S Theory and fuzzy logic.

  13. Real-Time Intrusion Detection System Framework Based on Conditional Random Fields%基于条件随机场的实时入侵检测系统框架实现

    顾佼佼; 姜文志; 粟飞; 胡文萱

    2011-01-01

    入侵检测系统(IDS)如今是网络的重要组成部分,现在各种无线网络及专用网络都已配备检测系统。随着网络技术的迅猛发展,入侵检测的技术已经从简单的签名匹配发展成能充分利用上下文信息的基于异常和混合的检测方式。为了从网络环境大量记录信息中正确有效地识别出入侵,提出一种基于层叠条件随机场模型的入侵检测框架,该框架针对4类不同攻击方式利用条件随机场模型分别进行识别训练,然后逐层进行入侵识别,提高了入侵检测系统的自适应性和可移植性,降低了系统的误报率和误检率,可高精度的识别各种攻击。实验结果表明,该框架可实时有效的识别攻击,启动响应机制进行处理。%Intrusion detection systems are now an essential component in the all kinds of network even including wireless ad hoc network. With the rapid advancement in the network technologies, the focus of intrusion detection has shifted from simple signature matching approaches to detecting attacks based on analyzing contextual information that employed in based on anomaly and hybrid intrusion detection approaches In order to correctly and effectively recognizing the hidden attack intrusion from large volume of low level system logs, a layered based on anomaly intrusion detection framework was proposed using conditional random fields to detect a wide variety of attacks. For models separately, and then processes the data layer fou by r classes of attack the framework trains four different layer to detect intrusion. Attacks could be identified and intrusion response could be initiated in real time with this framework and the system adaptability and portability were improved significantly reduce the system false alarm rate and false detection rate. Experiments show that the CRF model could detect attacks effectively

  14. A methodical and adaptive framework for Data Warehouse of Salary Management System

    Manzoor Ahmad

    2015-01-01

    Years of experience as an employee of University of Kashmir has always desired us to have a typical solution where most of the activities related to salary are fully automated without checking across the files whenever there is a need e.g. individual month‟s salary report , web based information submission, filing of returns , increment information etc. After thorough analysis , taking employee satisfaction , sensitivity and security of data , a long term solution was to develop a centralized...

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

    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.

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

    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.

  17. Application of Machine Learning Approaches in Intrusion Detection System: A Survey

    Nutan Farah Haq

    2015-03-01

    Full Text Available Network security is one of the major concerns of the modern era. With the rapid development and massive usage of internet over the past decade, the vulnerabilities of network security have become an important issue. Intrusion detection system is used to identify unauthorized access and unusual attacks over the secured networks. Over the past years, many studies have been conducted on the intrusion detection system. However, in order to understand the current status of implementation of machine learning techniques for solving the intrusion detection problems this survey paper enlisted the 49 related studies in the time frame between 2009 and 2014 focusing on the architecture of the single, hybrid and ensemble classifier design. This survey paper also includes a statistical comparison of classifier algorithms, datasets being used and some other experimental setups as well as consideration of feature selection step.

  18. Automated Signature Creator for a Signature Based Intrusion Detection System with Network Attack Detection Capabilities (Pancakes

    Frances Bernadette C. De Ocampo

    2015-05-01

    Full Text Available Signature-based Intrusion Detection System (IDS helps in maintaining the integrity of data in a network controlled environment. Unfortunately, this type of IDS depends on predetermined intrusion patterns that are manually created. If the signature database of the Signature-based IDS is not updated, network attacks just pass through this type of IDS without being noticed. To avoid this, an Anomaly-based IDS is used in order to countercheck if a network traffic that is not detected by Signature-based IDS is a true malicious traffic or not. In doing so, the Anomaly-based IDS might come up with several numbers of logs containing numerous network attacks which could possibly be a false positive. This is the reason why the Anomaly-based IDS is not perfect, it would readily alarm the system that a network traffic is an attack just because it is not on its baseline. In order to resolve the problem between these two IDSs, the goal is to correlate data between the logs of the Anomaly-based IDS and the packet that has been captured in order to determine if a network traffic is really malicious or not. With the supervision of a security expert, the malicious network traffic would be verified as malicious. Using machine learning, the researchers can identify which algorithm is better than the other algorithms in classifying if a certain network traffic is really malicious. Upon doing so, the creation of signatures would follow by basing the automated creation of signatures from the detected malicious traffic.

  19. Design and adaptation of ocean observing systems at coastal scales, the role of data assimilation in the optimization of measures.

    Brandini, Carlo; Taddei, Stefano; Fattorini, Maria; Doronzo, Bartolomeo; Lapucci, Chiara; Ortolani, Alberto; Poulain, Pierre Marie

    2015-04-01

    The design and the implementation of observation systems, in the current view, are not limited to the capability to observe some phenomena of particular interest in a given sea area, but must ensure maximum benefits to the analysis/prediction systems that are based on numerical models. The design of these experimental systems takes great advantage from the use of synthetic data, whose characteristics are as close as possible to the observed data (e.g. in-situ), in terms of spatial and temporal variability, particularly when the power spectrum of the observed signal is close to that reproduced by a numerical model. This method, usually referred to as OSSE (Observing System Simulation Experiment), is a preferred way to test numerical data for assimilation into models as if they were real data, with the advantage of defining different datasets for data assimilation at almost no cost. This applies both to the design of fixed networks (such as buoys or coastal radars), and to the improvement of the performance of mobile platforms, such as autonomous marine vehicles, floats or mobile radars, through the optimization of parameters for vehicle guidance, coverage, trajectories or localization of sampling points, according to the adaptive observation concept. In this work we present the results of some experimental activities recently undertaken in the coastal area between the Ligurian and Northern Tyrrhenian seas, that have shown a great vulnerability in recent years, due to a number of marine accidents and environmental issues. In this cross-border area an observation and forecasting system is being installed as part of the SICOMAR project (PO maritime Italy-France), in order to provide real time data at high spatial and time resolution, and to design interoperable, expandable and flexible observing platforms, that can be quickly adapted to the needs of local problems (e.g. accidents at sea). The starting SICOMAR network includes HF coastal radars, FerryBoxes onboard ships

  20. Network intrusion detection

    Oboile Tirelo; YANG Chun-hua

    2003-01-01

    Nowadays, network computer systems play an increasingly important role in society and economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is why the computer security has become an essential concern for network administrators. Too often, intrusions wreak havoc inside LANs and the time and cost to repair the damage can grow to extreme proportions. Instead of using passive measures to fix and patch security holes once they have been exploited, it is more effective to adopt a protective approach to intrusions. In addition to the well-established intrusion prevention techniques such as data encryption and message integrity, user authentication and user authorization, as well as the avoidance of security flaws inherent to many off-the-shelf applications, intrusion detection techniques can be viewed as an addition safeguard for network computers. The paper discusses traditional and new security designs, the approach to implementing best-practice security measures and the method to trace the malicious computer attackers.

  1. Volcano growth mechanisms and the role of sub-volcanic intrusions: Insights from 2D seismic reflection data

    Magee, Craig; Hunt-Stewart, Esther; Jackson, Christopher A.-L.

    2013-07-01

    Temporal and spatial changes in volcano morphology and internal architecture can determine eruption style and location. However, the relationship between the external and internal characteristics of volcanoes and sub-volcanic intrusions is often difficult to observe at outcrop or interpret uniquely from geophysical and geodetic data. We use high-quality 2D seismic reflection data from the Ceduna Sub-basin, offshore southern Australia, to quantitatively analyse 56, pristinely-preserved, Eocene-age volcanogenic mounds, and a genetically-related network of sub-volcanic sills and laccoliths. Detailed seismic mapping has allowed the 3D geometry of each mound to be reconstructed and distinct seismic facies within them to be recognised. Forty-six continental, basaltic shield volcanoes have been identified that have average flank dips of attributed to intrusions with complex morphologies; and/or (iii) reflect magma movement along pre-existing fracture systems. These complexities should therefore be considered in eruption forecasting models that link pre-eruption ground deformation to subterranean magma emplacement depth and volume. More generally, our study highlights the key role that seismic reflection data can play in understanding the geometry, distribution and evolution of ancient and modern volcanic systems.

  2. Enforcing positivity in intrusive PC-UQ methods for reactive ODE systems

    We explore the relation between the development of a non-negligible probability of negative states and the instability of numerical integration of the intrusive Galerkin ordinary differential equation system describing uncertain chemical ignition. To prevent this instability without resorting to either multi-element local polynomial chaos (PC) methods or increasing the order of the PC representation in time, we propose a procedure aimed at modifying the amplitude of the PC modes to bring the probability of negative state values below a user-defined threshold. This modification can be effectively described as a filtering procedure of the spectral PC coefficients, which is applied on-the-fly during the numerical integration when the current value of the probability of negative states exceeds the prescribed threshold. We demonstrate the filtering procedure using a simple model of an ignition process in a batch reactor. This is carried out by comparing different observables and error measures as obtained by non-intrusive Monte Carlo and Gauss-quadrature integration and the filtered intrusive procedure. The filtering procedure has been shown to effectively stabilize divergent intrusive solutions, and also to improve the accuracy of stable intrusive solutions which are close to the stability limits

  3. Detecting Danger: Applying a Novel Immunological Concept to Intrusion Detection Systems

    Greensmith, Julie; Twycross, Jamie

    2010-01-01

    In recent years computer systems have become increasingly complex and consequently the challenge of protecting these systems has become increasingly difficult. Various techniques have been implemented to counteract the misuse of computer systems in the form of firewalls, anti-virus software and intrusion detection systems. The complexity of networks and dynamic nature of computer systems leaves current methods with significant room for improvement. Computer scientists have recently drawn inspiration from mechanisms found in biological systems and, in the context of computer security, have focused on the human immune system (HIS). The human immune system provides a high level of protection from constant attacks. By examining the precise mechanisms of the human immune system, it is hoped the paradigm will improve the performance of real intrusion detection systems. This paper presents an introduction to recent developments in the field of immunology. It discusses the incorporation of a novel immunological parad...

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

    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.

  5. Building Real-Time Network Intrusion Detection System Based on Parallel Time-Series Mining Techniques

    Zhao Feng; Li Qinghua

    2005-01-01

    A new real-time model based on parallel time-series mining is proposed to improve the accuracy and efficiency of the network intrusion detection systems. In this model, multidimensional dataset is constructed to describe network events, and sliding window updating algorithm is used to maintain network stream. Moreover, parallel frequent patterns and frequent episodes mining algorithms are applied to implement parallel time-series mining engineer which can intelligently generate rules to distinguish intrusions from normal activities. Analysis and study on the basis of DAWNING 3000 indicate that this parallel time-series mining-based model provides a more accurate and efficient way to building real-time NIDS.

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

    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...

  7. Field data and numerical modeling: A multiple lines of evidence approach for assessing vapor intrusion exposure risks.

    Pennell, Kelly G; Scammell, Madeleine K; McClean, Michael D; Suuberg, Eric M; Moradi, Ali; Roghani, Mohammadyousef; Ames, Jennifer; Friguglietti, Leigh; Indeglia, Paul A; Shen, Rui; Yao, Yijun; Heiger-Bernays, Wendy J

    2016-06-15

    USEPA recommends a multiple lines of evidence approach to make informed decisions at vapor intrusion sites because the vapor intrusion pathway is notoriously difficult to characterize. Our study uses this approach by incorporating groundwater, soil gas, indoor air field measurements and numerical models to evaluate vapor intrusion exposure risks in a Metro-Boston neighborhood known to exhibit lower than anticipated indoor air concentrations based on groundwater concentrations. We collected and evaluated five rounds of field sampling data over the period of one year. Field data results show a steep gradient in soil gas concentrations near the groundwater surface; however as the depth decreases, soil gas concentration gradients also decrease. Together, the field data and the numerical model results suggest that a subsurface feature is limiting vapor transport into indoor air spaces at the study site and that groundwater concentrations are not appropriate indicators of vapor intrusion exposure risks in this neighborhood. This research also reveals the importance of including relevant physical models when evaluating vapor intrusion exposure risks using the multiple lines of evidence approach. Overall, the findings provide insight about how the multiple lines of evidence approach can be used to inform decisions by using field data collected using regulatory-relevant sampling techniques, and a well-established 3-D vapor intrusion model. PMID:26977535

  8. Salt Water Intrusion in a Three-dimensional Groundwater System in The Netherlands: a Numerical Study

    Oude Essink, Gualbert

    2001-01-01

    Salt water intrusion is investigated in a coastal groundwater system in the northern part of the province Noord-Holland, The Netherlands. Density dependent groundwater flow is modeled in three-dimensions withMOCDENS3D. This computer code is a version of MOC3D (Konikow et al., 1996) that has been ada

  9. Intrusion Detection System using Memtic Algorithm Supporting with Genetic and Decision Tree Algorithms

    K. P. Kaliyamurthie; D. Parameswari; R.M.Suresh

    2012-01-01

    This paper has proposed a technique of combining Decision Tree, Genetic Algorithm, DT-GA and Memtic algorithm to find more accurate models for fitting the behavior of network intrusion detection system. We simulate this sort of integrated algorithm and the results obtained with encouragement to further work.

  10. Analysis of Machine Learning Techniques for Intrusion Detection System: A Review

    Asghar Ali Shah; Malik Sikander Hayat Khiyal; Muhammad Daud Awan

    2015-01-01

    Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) is one of the major research problems in network security. IDSs are developed to detect both known and unknown attacks. There are many techniques used in IDS for protecting computers and networks from network based and host based attacks.

  11. Systematic adaptation of data delivery

    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.

  12. Using Learning Vector Quantization in Alert Management of Intrusion Detection System

    Amir Azimi Alasti Ahrabi; Kaveh Feyzi; Zahra Atashbar Orang; Hadi Bahrbegi; Elnaz Safarzadeh

    2012-01-01

    Intrusion detection system (IDS) is used to produce security alerts to discover attacks againstprotected network and/or computer systems. IDSs generate high amount of security alerts andanalyzing these alert by a security expert are time consuming and error pron. IDS alertmanagement system are used to manage generated alerts and classify true positive and falsepositives alert. This paper represents an IDS alert management system that uses learning vectorquantization technique to classify gene...

  13. A HYBRID INTRUSION PREVENTION SYSTEM (HIPS FOR WEB DATABASE SECURITY

    Eslam Mohsin Hassib

    2010-07-01

    Full Text Available Web database security is a challenging issue that should be taken into consideration when designing and building business based web applications. Those applications usually include critical processes such as electronic-commerce web applications that include money transfer via visa or master cards. Security is a critical issue in other web based application such as sites for military weapons companies and national security of countries. The main contributionof this paper is to introduce a new web database security model that includes a combination of triple system ; (i Host Identity protocol(HIP in a new authentication method called DSUC (Data Security Unique Code, (ii a strong filtering rules that detects intruders with high accuracy, and (iii a real time monitoring system that employs the Uncertainty Degree Model (UDM using fuzzy sets theory. It was shown that the combination of those three powerful security issues results in very strong security model. Accordingly, the proposed web database security model has the ability to detect and provide a real time prevention of intruder access with high precision. Experimental results have shown that the proposed model introduces satisfactory web database protection levels which reach in some cases to detect and prevent more that 93% of the intruders.

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

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

    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

  16. NON-INTRUSIVE REMOTE MONITORING OF SERVICES IN A DATA CENTRE

    Hemanta Kumar Kalita

    2011-07-01

    Full Text Available Non-intrusive remote monitoring of data centre services should be such that it does not require (or minimal modification of legacy code and standard practices. Also, allowing third party agent to sit on every server in a data centre is a risk from security perspective. Hence, use of standard such as SNMPv3 is advocated in this kind of environment. There are many tools (open source or commercial available which uses SNMP; but we observe that most of the tools do not have an essential feature for auto-discovery of network. In this paper we present an algorithm for remote monitoring of services in a data centre. The algorithm has two stages: 1 auto discovery of network topology and 2 data collection from remote machine. Further, we compare SNMP with WBEM and identify some other options for remote monitoring of services and their advantages and disadvantages.

  17. New Genetic Algorithm Based Intrusion Detection System for SCADA

    Aarcha Anoop

    2013-04-01

    Full Text Available Securing SCADA systems is a critical aspect of industrial systems. Industrial systems have installations which actively using the public network in order to provide new features and services which make the system unsecured .By introducing a filtering system ,we can analyse the critical state of the system which can be monitored and secure SCADA network protocols. But in this approach, there is no mathematical method for calculating filter parameters for DDOS, R2L, U2R attacks. In this paper, we present a new genetic algorithm based approach for calculating those parameters to make the system more secure.

  18. Non-Intrusive Magneto-Optic Detecting System for Investigations of Air Switching Arcs

    In current investigations of electric arc plasmas, experiments based on modern testing technology play an important role. To enrich the testing methods and contribute to the understanding and grasping of the inherent mechanism of air switching arcs, in this paper, a non-intrusive detecting system is described that combines the magneto-optic imaging (MOI) technique with the solution to inverse electromagnetic problems. The detecting system works in a sequence of main steps as follows: MOI of the variation of the arc flux density over a plane, magnetic field information extracted from the magneto-optic (MO) images, arc current density distribution and spatial pattern reconstruction by inverting the resulting field data. Correspondingly, in the system, an MOI set-up is designed based on the Faraday effect and the polarization properties of light, and an intelligent inversion algorithm is proposed that involves simulated annealing (SA). Experiments were carried out for high current (2 kA RMS) discharge cases in a typical low-voltage switchgear. The results show that the MO detection system possesses the advantages of visualization, high resolution and response, and electrical insulation, which provides a novel diagnostics tool for further studies of the arc. (low temperature plasma)

  19. Non-Intrusive Magneto-Optic Detecting System for Investigations of Air Switching Arcs

    Zhang, Pengfei; Zhang, Guogang; Dong, Jinlong; Liu, Wanying; Geng, Yingsan

    2014-07-01

    In current investigations of electric arc plasmas, experiments based on modern testing technology play an important role. To enrich the testing methods and contribute to the understanding and grasping of the inherent mechanism of air switching arcs, in this paper, a non-intrusive detecting system is described that combines the magneto-optic imaging (MOI) technique with the solution to inverse electromagnetic problems. The detecting system works in a sequence of main steps as follows: MOI of the variation of the arc flux density over a plane, magnetic field information extracted from the magneto-optic (MO) images, arc current density distribution and spatial pattern reconstruction by inverting the resulting field data. Correspondingly, in the system, an MOI set-up is designed based on the Faraday effect and the polarization properties of light, and an intelligent inversion algorithm is proposed that involves simulated annealing (SA). Experiments were carried out for high current (2 kA RMS) discharge cases in a typical low-voltage switchgear. The results show that the MO detection system possesses the advantages of visualization, high resolution and response, and electrical insulation, which provides a novel diagnostics tool for further studies of the arc.

  20. Space-time adaptive decision feedback neural receivers with data selection for high-data-rate users in DS-CDMA systems.

    de Lamare, Rodrigo C; Sampaio-Neto, Raimundo

    2008-11-01

    A space-time adaptive decision feedback (DF) receiver using recurrent neural networks (RNNs) is proposed for joint equalization and interference suppression in direct-sequence code-division multiple-access (DS-CDMA) systems equipped with antenna arrays. The proposed receiver structure employs dynamically driven RNNs in the feedforward section for equalization and multiaccess interference (MAI) suppression and a finite impulse response (FIR) linear filter in the feedback section for performing interference cancellation. A data selective gradient algorithm, based upon the set-membership (SM) design framework, is proposed for the estimation of the coefficients of RNN structures and is applied to the estimation of the parameters of the proposed neural receiver structure. Simulation results show that the proposed techniques achieve significant performance gains over existing schemes. PMID:18990643

  1. Modeling message sequences for intrusion detection in industrial control systems

    Caselli, Marco; Zambon, Emmanuele; Petit, Jonathan; Kargl, Frank; Rice, Mason; Shenoi, Sujeet

    2015-01-01

    Compared with standard information technology systems, industrial control systems show more consistent and regular communications patterns. This characteristic contributes to the stability of controlled processes in critical infrastructures such as power plants, electric grids and water treatment fa

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

    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

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

    Epstein Richard H; Wachtel Ruth E; Dexter Franklin

    2011-01-01

    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 dat...

  4. Using Site Testing Data for Adaptive Optics Simulations

    Herriot, Glen; Andersen, David; Conan, Rod; Ellerbroek, Brent; Gilles, Luc; Hickson, Paul; Jackson, Kate; Lardière, Olivier; Pfrommer, Thomas; Véran, Jean-Pierre; Wang, Lianqi

    2011-01-01

    Astronomical Site testing data plays a vital role in the simulation, design, evaluation and operation of adaptive optics systems for large telescope. We present the example of TMT and its first light facilitiy adaptive optics system NFIRAOS, and illustrate the many simulations done based on site testing data.

  5. PERFORMANCE COMPARISON OF INTRUSION DETECTION SYSTEM USING VARIOUS TECHNIQUES – A REVIEW

    S. Devaraju

    2013-09-01

    Full Text Available Nowadays, the security has become a critical part of any organization or industry information systems. The Intrusion Detection System is an effective method to deal with the new kind of threats such as DoS, Porbe, R2L and U2R. In this paper, we analyze the various approaches such as Hidden Semi Markov Model, Conditional Random Fields and Layered Approach, Bayesian classification, Data Mining techniques, Clustering Algorithms such as K-Means and Fuzzy c-Means, Back Propagation Neural Network, SOM Neural Network, Rough Set Neural Network Algorithm, Genetic Algorithm, Pattern Matching, Principle Component Analysis, Linear Discriminant Analysis, Independent Component Analysis, Multivariate Statistical Analysis, SOM/PSO algorithm etc. The performance is measured for two different datasets using various approaches. The datasets are trained and tested for identifying the new attacks that will affect the hosts or networks. The well known KDD Cup 1999 or DARPA 1999 dataset has been used to improve the accuracy and performance. The four groups of attacks are identified as Probe, DoS, U2R and R2L. The dataset used for training set is 494,021 and testing set is 311,028. The aim is to improve the detection rate and performance of the proposed system.

  6. Generating Representative Attack Test Cases for Evaluating and Testing Wireless Intrusion Detection Systems

    Khalid Nasr; Anas Abou El Kalam; Christian Fraboul

    2012-01-01

    Openness of wireless communication medium and flexibility in dealing with wireless communication protocols and their vulnerabilities create a problem of poor security. Due to deficiencies in the security mechanisms of the first line of defense such as firewall and encryption, there are growing interests in detecting wireless attacks through a second line of defense in the form of Wireless Intrusion Detection System (WIDS). WIDS monitors the radio spectrum and system activities and detects att...

  7. RISM -- Reputation Based Intrusion Detection System for Mobile Ad hoc Networks

    Trivedi, Animesh Kr; Kapoor, Rishi; Arora, Rajan; Sanyal, Sudip; Sanyal, Sugata

    2013-01-01

    This paper proposes a combination of an Intrusion Detection System with a routing protocol to strengthen the defense of a Mobile Ad hoc Network. Our system is Socially Inspired, since we use the new paradigm of Reputation inherited from human behavior. The proposed IDS also has a unique characteristic of being Semi-distributed, since it neither distributes its Observation results globally nor keeps them entirely locally; however, managing to communicate this vital information without accretio...

  8. Petrogenesis of the Ni-Cu-PGE sulfide-bearing Tamarack Intrusive Complex, Midcontinent Rift System, Minnesota

    Taranovic, Valentina; Ripley, Edward M.; Li, Chusi; Rossell, Dean

    2015-01-01

    The Tamarack Intrusive Complex (TIC, 1105.6 ± 1.2 Ma) in NE Minnesota, was emplaced during the early stages of the development of the Midcontinent Rift System (MRS, "Early Stage": 1110-1106 Ma). Country rocks of the TIC are those of the Paleoproterozoic Thomson Formation, part of the Animikie Group including sulfide-bearing metasedimentary black shale. The magmatic system is composed of at least two principal mafic-ultramafic intrusive sequences: the sulfide-barren Bowl Intrusion in the south and the "dike" area intrusions in the north which host Ni-Cu-Platinum Group Elements (PGE) mineralization with up to 2.33% Ni, 1.24% Cu, 0.34 g/t Pt, 0.23 g/t Pd and 0.18 g/t Au. Two distinct intrusive units in the "dike" area are the CGO (coarse-grained olivine-bearing) Intrusion, a sub-vertical dike-like body, and the overlying sub-horizontal FGO (fine-grained olivine-bearing) Intrusion. Both intrusions comprise peridotite, feldspathic peridotite, feldspathic pyroxenite, melatroctolite and melagabbro. Massive sulfides are volumetrically minor and mainly occur as lenses emplaced into the country rocks associated with both intrusions. Semi-massive (net-textured) sulfides are distributed at the core of the CGO Intrusion, surrounded by a halo of the disseminated sulfides. Disseminated sulfides also occur in lenses along the base of the FGO Intrusion. Olivine compositions in the CGO Intrusion are between Fo89 and Fo82 and in the FGO Intrusion from Fo84 to Fo82. TIC intrusions have more primitive olivine compositions than that of olivine in the sheet-like intrusions in the Duluth Complex (below Fo70), as well as olivine from the smaller, conduit-related, Eagle and East Eagle Intrusions in Northern Michigan (Fo86 to Fo75). The FeO/MgO ratios of the CGO and FGO Intrusion parental magmas, inferred from olivine compositions, are similar to those of picritic basalts erupted during the early stages of the MRS formation. Trace element ratios differ slightly from other intrusions in the

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

    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.

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

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

    2013-01-01

    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. PMID:23529146

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

    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.

  12. MULTI SCALE TIME SERIES PREDICTION FOR INTRUSION DETECTION

    G. Palanivel

    2014-01-01

    Full Text Available We propose an anomaly-based network intrusion detection system, which analyzes traffic features to detect anomalies. The proposed system can be used both in online as well as off-line mode for detecting deviations from the expected behavior. Although our approach uses network packet or flow data, it is general enough to be adaptable for use with any other network variable, which may be used as a signal for anomaly detection. It differs from most existing approaches in its use of wavelet transform for generating different time scales for a signal and using these scales as an input to a two-stage neural network predictor. The predictor predicts the expected signal value and labels considerable deviations from this value as anomalies. The primary contribution of our work would be to empirically evaluate the effectiveness of multi resolution analysis as an input to neural network prediction engine specifically for the purpose of intrusion detection. The role of Intrusion Detection Systems (IDSs, as special-purpose devices to detect anomalies and attacks in a network, is becoming more important. First, anomaly-based methods cannot achieve an outstanding performance without a comprehensive labeled and up-to-date training set with all different attack types, which is very costly and time-consuming to create if not impossible. Second, efficient and effective fusion of several detection technologies becomes a big challenge for building an operational hybrid intrusion detection system.

  13. Adaptive protection algorithm and system

    Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA

    2009-04-28

    An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.

  14. Realistic Prediction of BER for Adaptive OFDM Systems

    Luo, Meiling; Villemaud, Guillaume; Gorce, Jean-Marie; Jie ZHANG

    2013-01-01

    Adaptive OFDM systems improve the spectral efficiency. In this paper, block adaptive modulation is implemented based on the realistic prediction of BER and fading parameters from the MR-FDPF model. The aggregate data rate from block adaptive modulation is compared to that from non-adaptive modulation, and at the end, the data rate gain is obtained.

  15. Adaptive ant colony clustering method for intrusion detection%基于自适应蚁群聚类的入侵检测

    杨照峰; 樊爱京; 樊爱宛

    2011-01-01

    For the problem that partial data partition is not accurate enough in clustering results of ant colony clustering algorithm, an improved adaptive chaotic ant colony clustering algorithm based on information entropy is proposed. The algorithm measures the evolutive degree by optimizing the population information entropy,and adjusts the pheromone update strategy adaptively. It uses the chaotic search operator to search better solution near current global optimal solution at the end of each iteration.With progress of the algorithm,search range of the chaotic operator is gradually reduced so that chaotic operator avoids falling into local optimum in the initial period and improves search precision in the later period of ant colony search. This leads to better clustering results.Using the KDD Cup 1999 intrusion detection data, simulation results show that the clustering effect improves significantly,and can effectively improve the detection rate of intrusion detection and reduce the false detection rate.%针对蚁群聚类算法在聚类结果中出现部分数据划分不够准确的问题,提出一种基于信息熵调整的自适应混沌蚁群聚类改进算法.该算法通过优化过程中种群的信息熵来衡量演化的程度,自适应地调整信息素更新策略.每一次迭代结束时,使用混沌搜索算子在当前全局最优解附近搜索更好的解.而随着算法的进行,混沌算子搜索范围逐渐缩小,这样混沌算子在蚁群搜索的初期起到防止陷入局部最优的作用,在蚁群搜索后期起到提高搜索精度的作用,从而得到更好的聚类结果.使用 KDDCup 1999 入侵检测数据集所作的仿真实验结果表明,聚类效果改进明显,并能有效提高入侵检测的检测率、降低误检率.

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

    Maya Louk; Hyotaek Lim; HoonJae Lee

    2014-01-01

    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 protecti...

  17. How to secure web servers by the intrusion prevention system (IPS?

    Yousef Farhaoui

    2016-03-01

    Full Text Available Information technology and especially the Internet are playing an increasing role in our society. Approaches by signature show limits on intrusion detection / attacks by the fact that most web vulnerabilities are specifically for specific applications may be developed in-house by companies. Behavioral methods are therefore an interesting approach in this area. An IPS (Intrusion Prevention System is a tool that is used to enhance the security level. We present here the secure IPS architecture web server. We will also discuss measures that define the effectiveness of our IPS and very recent work of standardization and homogenization of our IPS platform. The approach relies on preventive mechanisms: it is then to develop devices capable of preventing any action that would result in a violation of the security policy. However, experienceand results shows that it is impossible to build a fully secure system for technical or practical reasons.

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

    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

  19. Distributed Intrusion Detection Systems for Enhancing Security in Mobile Wireless Sensor Networks

    Leonardo Mostarda; Alfredo Navarra

    2008-01-01

    We present an approach to provide Intrusion Detection Systems (IDS) facilities into Wireless Sensors Networks (WSN). WSNs are usually composed of a large number of low power sensors. They require a careful consumption of the available energy in order to prolong the lifetime of the network. From the security point of view, the overhead added to standard protocols must be as light as possible according to the required security level. Starting from the DESERT tool [14, 16, 25] which has been pro...

  20. Analysis of Fuzzy Logic Based Intrusion Detection Systems in Mobile Ad Hoc Networks

    Chaudhary, A.; V. N. Tiwari; Kumar, A

    2014-01-01

    Due to the advancement in wireless technologies, many of new paradigms have opened for communications. Among these technologies, mobile ad hoc networks play a prominent role for providing communication in many areas because of its independent nature of predefined infrastructure. But in terms of security, these networks are more vulnerable than the conventional networks because firewall and gateway based security mechanisms cannot be applied on it. That’s why intrusion detection systems are us...

  1. Co-operative Wireless Intrusion Detection System Using MIBs From SNMP

    Ashvini Vyavhare; Varsharani Bhosale; Mrunal Sawant; Fazila Girkar

    2012-01-01

    In emerging technology of Internet, security issues are becoming more challenging. In case of wired LAN it is somewhat in control, but in case of wireless networks due to exponential growth in attacks, it has made difficult to detect such security loopholes. Wireless network security is being addressed using firewalls, encryption techniques and wired IDS (Intrusion Detection System) methods. But the approaches which were used in wired network were not successful in producing effective results...

  2. Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks

    Nabil Ali Alrajeh; Lloret, J

    2013-01-01

    Intrusion detection system (IDS) is regarded as the second line of defense against network anomalies and threats. IDS plays an important role in network security. There are many techniques which are used to design IDSs for specific scenario and applications. Artificial intelligence techniques are widely used for threats detection. This paper presents a critical study on genetic algorithm, artificial immune, and artificial neural network (ANN) based IDSs techniques used in wireless sensor netw...

  3. HIERARCHICAL DESIGN BASED INTRUSION DETECTION SYSTEM FOR WIRELESS AD HOC SENSOR NETWORK

    Mohammad Saiful Islam Mamun; A.F.M. Sultanul Kabir

    2010-01-01

    In recent years, wireless ad hoc sensor network becomes popular both in civil and military jobs.However, security is one of the significant challenges for sensor network because of their deploymentin open and unprotected environment. As cryptographic mechanism is not enough to protect sensornetwork from external attacks, intrusion detection system needs to be introduced. Though intrusionprevention mechanism is one of the major and efficient methods against attacks, but there might besome atta...

  4. Fortifying Intrusion Detection Systems in Dynamic Ad Hoc and Wireless Sensor Networks

    Abdelouahid Derhab; Abdelghani Bouras; Mustapha Reda Senouci; Muhammad Imran

    2014-01-01

    We investigate three aspects of dynamicity in ad hoc and wireless sensor networks and their impact on the efficiency of intrusion detection systems (IDSs). The first aspect is magnitude dynamicity, in which the IDS has to efficiently determine whether the changes occurring in the network are due to malicious behaviors or or due to normal changing of user requirements. The second aspect is nature dynamicity that occurs when a malicious node is continuously switching its behavior between normal...

  5. Policy based intrusion detection and response system in hierarchical WSN architecture

    Mamun, Mohammad Saiful Islam; Kabir, A. F. M Sultanul; Hossen, Md. Sakhawat; Khan, Md. Razib Hayat

    2012-01-01

    In recent years, wireless sensor network becomes popular both in civil and military jobs. However, security is one of the significant challenges for sensor network because of their deployment in open and unprotected environment. As cryptographic mechanism is not enough to protect sensor network from external attacks, intrusion detection system (IDS) needs to be introduced. In this paper we propose a policy based IDS for hierarchical architecture that fits the current demands and restrictions ...

  6. A Survey of Recent Intrusion Detection Systems for Wireless Sensor Network

    Bhattasali, Tapalina; Chaki, Rituparna

    2012-01-01

    Security of Wireless sensor network (WSN) becomes a very important issue with the rapid development of WSN that is vulnerable to a wide range of attacks due to deployment in the hostile environment and having limited resources. Intrusion detection system is one of the major and efficient defensive methods against attacks in WSN. A particularly devastating attack is the sleep deprivation attack, where a malicious node forces legitimate nodes to waste their energy by resisting the sensor nodes ...

  7. Multi-level and Secured Agent-based Intrusion Detection System

    Sodiya, Adesina Simon

    2006-01-01

    Since Intrusion Detection System (IDS) has become necessary security tool for detecting attacks on computer network and resources, it is therefore essential to improve on previous designs. In past, many mobile agent-based IDSs have been designed, but there still exists some drawbacks. Some of these drawbacks are low detection efficiency, high false alarm rate and agent security. A multi-level and secured IDS architecture that is based on mobile agent is presented on this work to correct these...

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

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

    2014-01-01

    In this work, a dynamic MATLAB Simulink model of a H3-350 Reformed Methanol Fuel Cell (RMFC) stand-alone battery charger produced by Serenergy is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseou...

  9. State-Based Network Intrusion Detection Systems for SCADA Protocols: A Proof of Concept

    Carcano, Andrea; Fovino, Igor Nai; Masera, Marcelo; Trombetta, Alberto

    We present a novel Intrusion Detection System able to detect complex attacks to SCADA systems. By complex attack, we mean a set of commands (carried in Modbus packets) that, while licit when considered in isolation on a single-packet basis, interfere with the correct behavior of the system. The proposed IDS detects such attacks thanks to an internal representation of the controlled SCADA system and a corresponding rule language, powerful enough to express the system's critical states. Furthermore, we detail the implementation and provide experimental comparative results.

  10. Adaptive web data extraction policies

    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.

  11. 3D modeling of a dolerite intrusion from the photogrammetric and geophysical data integration.

    Duarte, João; Machadinho, Ana; Figueiredo, Fernando; Mira, Maria

    2015-04-01

    The aims of this study is create a methodology based on the integration of data obtained from various available technologies, which allow a credible and complete evaluation of rock masses. In this particular case of a dolerite intrusion, which deployed an exploration of aggregates and belongs to the Jobasaltos - Extracção e Britagem. S.A.. Dolerite intrusion is situated in the volcanic complex of Serra de Todo-o-Mundo, Casais Gaiola, intruded in Jurassic sandstones. The integration of the surface and subsurface mapping, obtained by technology UAVs (Drone) and geophysical surveys (Electromagnetic Method - TEM 48 FAST), allows the construction of 2D and 3D models of the study local. The combination of the 3D point clouds produced from two distinct processes, modeling of photogrammetric and geophysical data, will be the basis for the construction of a single model of set. The rock masses in an integral perspective being visible their development above the surface and subsurface. The presentation of 2D and 3D models will give a perspective of structures, fracturation, lithology and their spatial correlations contributing to a better local knowledge, as well as its potential for the intended purpose. From these local models it will be possible to characterize and quantify the geological structures. These models will have its importance as a tool to assist in the analysis and drafting of regional models. The qualitative improvement in geological/structural modeling, seeks to reduce the value of characterization/cost ratio, in phase of prospecting, improving the investment/benefit ratio. This methodology helps to assess more accurately the economic viability of the projects.

  12. Query Adaptive Image Retrieval System

    Amruta Dubewar

    2014-03-01

    Full Text Available Images play a crucial role in various fields such as art gallery, medical, journalism and entertainment. Increasing use of image acquisition and data storage technologies have enabled the creation of large database. So, it is necessary to develop appropriate information management system to efficiently manage these collections and needed a system to retrieve required images from these collections. This paper proposed query adaptive image retrieval system (QAIRS to retrieve images similar to the query image specified by user from database. The goal of this system is to support image retrieval based on content properties such as colour and texture, usually encoded into feature vectors. In this system, colour feature extracted by various techniques such as colour moment, colour histogram and autocorrelogram and texture feature extracted by using gabor wavelet. Hashing technique is used to embed high dimensional image features into hamming space, where search can be performed by hamming distance of compact hash codes. Depending upon minimum hamming distance it returns the similar image to query image.

  13. A survey on anomaly and signature based intrusion detection system (IDS

    Mrs.Anshu Gangwar

    2014-04-01

    Full Text Available Security is considered as one of the most critical parameter for the acceptance of any networking technology. Information in transit must be protected from unauthorized release and modification, and the connection itself must be established and maintained securely malicious users have taken advantage of this to achieve financial gain or accomplish some corporate or personal agenda. Denial of Service (DoS and distributed DoS (DDoS attacks are evolving continuously. These attacks make network resources unavailable for legitimate users which results in massive loss of data, resources and money. Combination of Intrusion detection System and Firewall is used by Business Organizations to detect and p revent Organizations‟ network from these attacks. Signatures to detect them are not available. This paper presents a light-Weight mechanism to detect novel DoS/DDoS (Resource Consumption attacks and automatic signature generation process to represent them in real time. Experimental results are provided to support the proposed mechanism.

  14. Development of Embedded Based System to Monitor Elephant Intrusion in Forest Border Areas Using Internet of Things

    R. K. Vigneshwar

    2016-07-01

    Full Text Available The new era of computing technology is emerging as it will encompass every aspects of our lives with amazing potentials and it can be termed as Internet of Things (IOT. The IOT generally comprised of smart machines interacting and interactive with other machines, objects, environments and infrastructures. In embedded computing system each thing is uniquely identifiable but it is able to be interoperable within the existing internet infrastructure in IOT. As a result, massive volumes of data are being created, and that data is being processed into useful actions that can “command and control” things to make our living much comfortable and safer—and to ease our impact on the environment. In this paper we have proposed a elephant intrusion monitoring system using IOT. The various drawbacks in already existing system using embedded systems can be overcome as we have cloud based services, low cost and advanced miniaturization in packaging technology. Here we are developing a prototype model for real time interaction of elephant intrusion in forest border areas that allows a persistent monitoring by making use of an On board computer and cloud services.

  15. Geophysical characterization of hydrothermal systems and intrusive bodies, El Chichón volcano (Mexico)

    Jutzeler, Martin; Varley, Nick; Roach, Michael

    2011-04-01

    The 1982 explosive eruptions of El Chichón volcano (Chiapas, Mexico) destroyed the inner dome and created a 1-km-wide and 180-m-deep crater within the somma crater. A shallow hydrothermal system was exposed to the surface of the new crater floor and is characterized by an acid crater lake, a geyser-like Cl-rich spring (soap pool), and numerous fumarole fields. Multiple geophysical surveys were performed to define the internal structure of the volcanic edifice and its hydrothermal system. We carried out a high-resolution ground-based geomagnetic survey in the 1982 crater and its surroundings and 38 very low frequency (VLF) transects around the crater lake. A 3-D inversion of the ground-based magnetic data set highlighted three high-susceptibility isosurfaces, interpreted as highly magnetized bodies beneath the 1982 crater floor. Inversion of a digitized regional aeromagnetic map highlighted four major deeply rooted cryptodomes, corresponding to major topographic highs and massive lava dome outcrops outside and on the somma rim. The intracrater magnetic bodies correspond closely to the active hydrothermal vents and their modeled maximum basal depth matches the elevation of the springs on the flanks of the volcano. Position, dip, and vertical extent of active and extinct hydrothermal vents identified by VLF-EM surveys match the magnetic data set. We interpret the shallow lake spring hydrothermal system to be mostly associated with buried remnants of the 550 BP dome, but the Cl-rich soap pool may be connected to a small intrusion emplaced at shallow depth during the 1982 eruption.

  16. Co-operative Wireless Intrusion Detection System Using MIBs From SNMP

    Ashvini Vyavhare

    2012-03-01

    Full Text Available In emerging technology of Internet, security issues are becoming more challenging. In case of wired LAN it is somewhat in control, but in case of wireless networks due to exponential growth in attacks, it has made difficult to detect such security loopholes. Wireless network security is being addressed using firewalls, encryption techniques and wired IDS (Intrusion Detection System methods. But the approaches which were used in wired network were not successful in producing effective results for wireless networks. It is so because of features of wireless network such as open medium, dynamic changing topology, cooperative algorithms, lack of centralized monitoring and management point, and lack of a clear line of defense etc. So, there is need for new approach which will efficiently detect intrusion in wireless network. Efficiency can be achieved by implementing distributive, co-operative based, multi-agent IDS. The proposed system supports all these three features. It includes mobile agents for intrusion detection which uses SNMP (Simple network Management Protocol and MIB (Management Information Base variables for mobile wireless networks

  17. Intrusion Detection System for Mobile Ad - Hoc Network Using Cluster-Based Approach

    Nisha Dang

    2012-06-01

    Full Text Available Today Mobile Ad-hoc Networks have wide spread use in normal as well as mission critical applications. Mobile ad hoc networks are more likely to be attacked due to lack of infrastructure and no central management. To secure Manets many traditional security solutions like encryption are used but not find to be promising. Intrusion detection system is one of the technologies that provide some goodsecurity solutions. IDS provide monitoring and auditing capabilities to detect any abnormality in security of the system. IDS can be used with clustering algorithms to protect entire cluster from malicious code. Existing clustering algorithms have a drawback of consuming more power and they are associated with routes. The routeestablishment and route renewal affects the clusters and asa consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore IDS cannot be run on all the nodes. A trusted monitoring node can be deployed to detect and respond against intrusions in time. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes inthe network.

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

    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…

  19. Power-Aware Hybrid Intrusion Detection System (PHIDS) using Cellular Automata in Wireless AdHoc Networks

    Sree, Pokkuluri Kiran; Babu, Inampudi Ramesh

    2013-01-01

    Adhoc wireless network with their changing topology and distributed nature are more prone to intruders. The network monitoring functionality should be in operation as long as the network exists with nil constraints. The efficiency of an Intrusion detection system in the case of an adhoc network is not only determined by its dynamicity in monitoring but also in its flexibility in utilizing the available power in each of its nodes. In this paper we propose a hybrid intrusion detection system, b...

  20. Adaptive System Modeling for Spacecraft Simulation

    Thomas, Justin

    2011-01-01

    This invention introduces a methodology and associated software tools for automatically learning spacecraft system models without any assumptions regarding system behavior. Data stream mining techniques were used to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). Evaluation on historical ISS telemetry data shows that adaptive system modeling reduces simulation error anywhere from 50 to 90 percent over existing approaches. The purpose of the methodology is to outline how someone can create accurate system models from sensor (telemetry) data. The purpose of the software is to support the methodology. The software provides analysis tools to design the adaptive models. The software also provides the algorithms to initially build system models and continuously update them from the latest streaming sensor data. The main strengths are as follows: Creates accurate spacecraft system models without in-depth system knowledge or any assumptions about system behavior. Automatically updates/calibrates system models using the latest streaming sensor data. Creates device specific models that capture the exact behavior of devices of the same type. Adapts to evolving systems. Can reduce computational complexity (faster simulations).

  1. Some intrusions in dietary reports by fourth-grade children are based on specific memories: data from a validation study of the effect of interview modality

    Smith, Albert F.; Baxter, Suzanne Domel; Hardin, James W.; Royer, Julie A.; Guinn, Caroline H

    2008-01-01

    In dietary recall for a specified target period, an intrusion denotes an item reported eaten that was not consumed during that period. Intrusions may denote items available during the specified period, items consumed during other periods, or items from general knowledge of dietary intake. To investigate a cognitive basis of intrusions, we analyzed data from a dietary-reporting validation study in which 69 fourth-grade children were observed eating two school meals (breakfast; lunch) and inter...

  2. A Novel Immune System Model and Its Application to Network Intrusion Detection

    Ling Jun; Cao Yang; Yin Jian-hua; Huang Tian-xi

    2003-01-01

    Based on analyzing the techniques and architec-ture of existing network Intrusion Detection System (IDS),and probing into the fundament of Immune System (IS), a novel immune model is presented and applied to network IDS,which is helpful to design an effective IDS. Besides, this pa-per suggests a scheme to represent the self profile of network.And an automated self profile extraction algorithm is provided to extract self profile from packets. The experimental results prove validity of the scheme and algorithm, which is the foundation of the immune model.

  3. A surrogate model for simulation-optimization of aquifer systems subjected to seawater intrusion

    Hussain, Mohammed S.; Javadi, Akbar A.; Ahangar-Asr, Alireza; Farmani, Raziyeh

    2015-04-01

    This study presents the application of Evolutionary Polynomial Regression (EPR) as a pattern recognition system to predicate the behavior of nonlinear and computationally complex aquifer systems subjected to seawater intrusion (SWI). The developed EPR models are integrated with a multi objective genetic algorithm to examine the efficiency of different arrangements of hydraulic barriers in controlling SWI. The objective of the optimization is to minimize the economic and environmental costs. The developed EPR model is trained and tested for different control scenarios, on sets of data including different pumping patterns as inputs and the corresponding set of numerically calculated outputs. The results are compared with those obtained by direct linking of the numerical simulation model with the optimization tool. The results of the two above-mentioned simulation-optimization (S/O) strategies are in excellent agreement. Three management scenarios are considered involving simultaneous use of abstraction and recharge to control SWI. Minimization of cost of the management process and the salinity levels in the aquifer are the two objective functions used for evaluating the efficiency of each management scenario. By considering the effects of the unsaturated zone, a subsurface pond is used to collect the water and artificially recharge the aquifer. The distinguished feature of EPR emerges in its application as the metamodel in the S/O process where it significantly reduces the overall computational complexity and time. The results also suggest that the application of other sources of water such as treated waste water (TWW) and/or storm water, coupled with continuous abstraction of brackish water and its desalination and use is the most cost effective method to control SWI. A sensitivity analysis is conducted to investigate the effects of different external sources of recharge water and different recovery ratios of desalination plant on the optimal results.

  4. Adapting bioinformatics curricula for big data.

    Greene, Anna C; Giffin, Kristine A; Greene, Casey S; Moore, Jason H

    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

  5. Dynamic Multi Layer Signature based Intrusion Detection system Using Mobile Agents

    Uddin, Mueen

    2010-01-01

    Intrusion detection systems have become a key component in ensuring the safety of systems and networks. As networks grow in size and speed continues to increase, it is crucial that efficient scalable techniques should be developed for IDS systems. Signature based detection is the most extensively used threat detection technique for Intrusion Detection Systems (IDS). One of the foremost challenges for signaturebased IDS systems is how to keep up with large volume of incoming traffic when each packet needs to be compared with every signature in the database. When an IDS cannot keep up with the traffic flood, all it can do is to drop packets, therefore, may miss potential attacks. This paper proposes a new model called Dynamic Multi-Layer Signature based IDS using Mobile Agents, which can detect imminent threats with very high success rate by dynamically and automatically creating and using small and efficient multiple databases, and at the same time, provide mechanism to update these small signature databases a...

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

    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...

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

    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. PMID:25750065

  8. An Useful Communication Mechanism for Distributed Agents-Based Intrusion Detection System

    DU Ye

    2006-01-01

    The communication mechanism plays an important role in an intrusion detection system, while it has not been paid enough attention. Based on analyzing the actual facts and expatiating upon the requirements a communication mechanism needs to meet, a message driven communication mechanism is proposed in this paper. The protocol presented here is divided into three layers: entity level, host level, and network level. The communication processes are also designed in detail. Experiments illustrate that cooperative entities can detect distributed sophisticated attacks accurately. Furthermore, this mechanism has the advantages like high reliability, low time delay and expenses.

  9. Classification Model with High Deviation for Intrusion Detection on System Call Traces

    2005-01-01

    A new classification model for host intrusion detection based on the unidentified short sequences and RIPPER algorithm is proposed. The concepts of different short sequences on the system call traces are strictly defined on the basis of in-depth analysis of completeness and correctness of pattern databases. Labels of short sequences are predicted by learned RIPPER rule set and the nature of the unidentified short sequences is confirmed by statistical method. Experiment results indicate that the classification model increases clearly the deviation between the attack and the normal traces and improves detection capability against known and unknown attacks.

  10. A WSN-Based Intrusion Alarm System to Improve Safety in Road Work Zones

    Jose Martin

    2016-01-01

    Full Text Available Road traffic accidents are one of the main causes of death and disability worldwide. Workers responsible for maintaining and repairing roadways are especially prone to suffer these events, given their exceptional exposure to traffic. Since these actuations usually coexist with regular traffic, an errant driver can easily intrude the work area and provoke a collision. Some authors have proposed mechanisms aimed at detecting breaches in the work zone perimeter and alerting workers, which are collectively called intrusion alarm systems. However, they have several limitations and have not yet fulfilled the necessities of these scenarios. In this paper, we propose a new intrusion alarm system based on a Wireless Sensor Network (WSN. Our system is comprised of two main elements: vehicle detectors that form a virtual barrier and detect perimeter breaches by means of an ultrasonic beam and individual warning devices that transmit alerts to the workers. All these elements have a wireless communication interface and form a network that covers the whole work area. This network is in charge of transmitting and routing the alarms and coordinates the behavior of the system. We have tested our solution under real conditions with satisfactory results.

  11. A Novel Method for Intrusion Detection System to Enhance Security in Ad hoc Network

    Bathla, Himani

    2010-01-01

    The notion of an ad hoc network is a new paradigm that allows mobile hosts (nodes) to communicate without relying on a predefined infrastructure to keep the network connected. Most nodes are assumed to be mobile and communication is assumed to be wireless. The mobility of nodes in an ad-hoc network means that both the population and the topology of the network are highly dynamic. It is very difficult to design a once-for-all intrusion detection system. A secure protocol should atleast include mechanisms against known attack types. In addition, it should provide a scheme to easily add new security features in the future. The paper includes the detailed description of Proposed Intrusion Detection System based on Local Reputation Scheme. The proposed System also includes concept of Redemption and Fading these are mechanism that allow nodes previously considered malicious to become a part of the network again. The simulation of the proposed system is to be done using NS-2 simulator.

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

    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.

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

    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.

  14. Services-oriented architecture for adaptive and intelligent data acquisition and processing systems in long pulse fusion experiments

    Advanced software tools for implementing nodes in distributed data acquisition systems (DDAQ) are essential for implementing long duration experiments. Nodes need local processing capabilities for implementing 'on line' and 'real time' analysis. Data reduction techniques and pattern recognitions solutions can be implemented in ITMS (Intelligent Test and Measurement System). User's processing algorithms are implemented in a high level graphical language (LabVIEW). DAQ must be integrated in complex network using SOA solutions. JINI provides this mechanism and simplifies use, setup, supervision and software update. Advanced timing and synchronization are essential tools in the next generation of advanced DAQs and SCXML is a 'powerful' tool for implementing Intelligent DAQ systems for long pulse fusion experiments

  15. Adaptive, dynamic, and resilient systems

    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

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

    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.

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

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

    2014-01-01

    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. PMID:25268920

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

    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

  19. Design of no blind area perimeter intrusion recognition system based on fisheye lens

    Dai, Jun-jian; Han, Wen-bo

    2013-08-01

    The Perimeter intrusion recognition technology has slowly become an indispensable function in the intelligent video surveillance system. The existed always use the multiple video acquisition nodes to respectively control a monitoring area and each node alarm independently. However, the existed solutions are difficult to avoid the existence of monitoring blind area, and can't suitable for the perimeter environment with irregular outline, and at the same time, because of the too many nodes, it inevitably decreased the overall accuracy of intrusion recognition system and increased the cost of system. To avoid the above defects, this paper mainly talks about the following three aspects. Firstly, we used the fisheye lens as the optical system of video acquisition node, and it evidently enhances each node's information acquisition ability. And in this way, we just need to decorate a small amount of video acquisition node to get no blind area environmental information of the perimeter when against a larger monitoring situation. Secondly, due to the inexistence of blind area, the system will have enough video image information to generate the 360 degree panoramic image for monitoring environment, and finally the system server collected the wide-angle image information to splice into the panoramic video image. Finally, the system will use the panoramic image to complete the intrusion behavior recognition, thus we can effectively avoid the parallel computation in many nodes independently invasion of recognition, and this can greatly reduces the dependence for the multiple CPU operation platform and enhances the reliability of the system. The field test results show that, with the help of this paper's solution, the perimeter of the invasion of recognition system can effectively avoids the recognition of blind area. In the same recognition algorithm and same level delay premise, it greatly reduces the monitoring system server configuration requirements, especially for the

  20. A Survey of Recent Intrusion Detection Systems for Wireless Sensor Network

    Bhattasali, Tapalina

    2012-01-01

    Security of Wireless sensor network (WSN) becomes a very important issue with the rapid development of WSN that is vulnerable to a wide range of attacks due to deployment in the hostile environment and having limited resources. Intrusion detection system is one of the major and efficient defensive methods against attacks in WSN. A particularly devastating attack is the sleep deprivation attack, where a malicious node forces legitimate nodes to waste their energy by resisting the sensor nodes from going into low power sleep mode. The goal of this attack is to maximize the power consumption of the target node, thereby decreasing its battery life. Existing works on sleep deprivation attack have mainly focused on mitigation using MAC based protocols, such as S-MAC, T-MAC, B-MAC, etc. In this article, a brief review of some of the recent intrusion detection systems in wireless sensor network environment is presented. Finally, we propose a framework of cluster based layered countermeasure that can efficiently mitig...

  1. A Semi-distributed Reputation Based Intrusion Detection System for Mobile Adhoc Networks

    Trivedi, Animesh Kr; Kapoor, Rishi; Sanyal, Sudip; Sanyal, Sugata

    2010-01-01

    A Mobile Adhoc Network (MANET) is a cooperative engagement of a collection of mobile nodes without any centralized access point or infrastructure to coordinate among the peers. The underlying concept of coordination among nodes in a cooperative MANET has induced in them a vulnerability to attacks due to issues like lack of fixed infrastructure, dynamically changing network topology, cooperative algorithms, lack of centralized monitoring and management point, and lack of a clear line of defense. We propose a semi-distributed approach towards Reputation Based Intrusion Detection System (IDS) that combines with the DSR routing protocol for strengthening the defense of a MANET. Our system inherits the features of reputation from human behavior, hence making the IDS socially inspired. It has a semi-distributed architecture as the critical observation results of the system are neither spread globally nor restricted locally. The system assigns maximum weightage to self observation by nodes for updating any reputatio...

  2. COMPUTER INTRUSION DETECTION BY TWOOBJECTIVE FUZZY GENETIC ALGORITHM

    Madhuri Agravat; Udai Pratap Rao

    2011-01-01

    The purpose of this paper is to describe two objective fuzzy genetics-based learning algorithms and discusses its usage to detect intrusion in a computer network. Experiments were performed with KDD-cup data set, which have information on computer networks, during normal behavior and intrusive behavior. The performance of final fuzzy classification system has been investigated using intrusion detection problem as a high dimensional classification problem. This task is formulate...

  3. A simplified adaptive optics system

    Ivanescu, Liviu; Racine, René; Nadeau, Daniel

    2003-02-01

    Affordable adaptive optics on small telescopes allow to introduce the technology to a large community and provide opportunities to train new specialists in the field. We have developed a low order, low cost adaptive optics system for the 1.6m telescope of the Mont Megantic Observatory. The system corrects tip-tilt, focus, astigmatisms and one trefoil term. It explores a number of new approaches. The sensor receives a single out-of-focus image of the reference star. The central obstruction of the telescope can free the focus detection from the effect of seeing and allows a very small defocus. The deformable mirror is profiled so as to preserve a parabolic shape under pressure from actuators located at its edge. A separate piezoelectric platform drives the tilt mirror.

  4. Adaptive Control Applied to Financial Market Data

    Šindelář, Jan; Kárný, Miroslav

    Strasbourg cedex: European Science Foundation, 2007, s. 1-6. [Advanced Mathematical Methods for Finance. Vídeň (AT), 17.09.2007-22.09.2007] R&D Projects: GA MŠk(CZ) 2C06001 Institutional research plan: CEZ:AV0Z10750506 Keywords : bayesian statistics * portfolio optimization * finance * adaptive control Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2007/si/sindelar-adaptive control applied to financial market data.pdf

  5. Three sided complex adaptative systems

    D'Hulst, R

    1999-01-01

    We introduce two three sided adaptative systems as toy models to mimic the exchange of commodities between buyers and sellers. These models are simple extensions of the minority game, exhibiting similar behaviour as well as some new features. The main difference between our two models is that in the first the three sides are equivalent while in the second, one choice appears as a compromise between the two other sides. Both models are investigated numerically and compared with the original minority game.

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

    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 selection based on Kullback-Leibner information is an alternative

  7. 基于轻负载代理的协同分布式入侵检测系统%Lightweight Agent for Collaborative Distribution Intrusion Detection System

    张琨; 刘凤玉

    2003-01-01

    The LAFCDIDS (Lightweight Agent for Collaborative Distnbution Intrusion Detection System) presented in this paper is a distributed intrusion detection system with the ability of collaborative detection in real time. The hierarchy architecture of agents and the ability of collaborative detection in real time are evident characteristics of the LAFCDIDS. Lightweight agent and agent sensitivity are LAFCDIDS's new concepts, which can reduce the overload of protected system, shorten the period of intrusion detection, and are suitable for monitoring the distributed collaborating attacks.

  8. An Ontology for Identifying Cyber Intrusion Induced Faults in Process Control Systems

    Hieb, Jeffrey; Graham, James; Guan, Jian

    This paper presents an ontological framework that permits formal representations of process control systems, including elements of the process being controlled and the control system itself. A fault diagnosis algorithm based on the ontological model is also presented. The algorithm can identify traditional process elements as well as control system elements (e.g., IP network and SCADA protocol) as fault sources. When these elements are identified as a likely fault source, the possibility exists that the process fault is induced by a cyber intrusion. A laboratory-scale distillation column is used to illustrate the model and the algorithm. Coupled with a well-defined statistical process model, this fault diagnosis approach provides cyber security enhanced fault diagnosis information to plant operators and can help identify that a cyber attack is underway before a major process failure is experienced.

  9. Mobile Agent Based Hierarchical Intrusion Detection System in Wireless Sensor Networks

    Surraya Khanum

    2012-01-01

    Full Text Available Security mechanism is a fundamental requirement of wireless networks in general and Wireless Sensor Networks (WSN in particular. Therefore, it is necessary that this security concern must be articulate right from the beginning of the network design and deployment. WSN needs strong security mechanism as it is usually deployed in a critical, hostile and sensitive environment where human labour is usually not involved. However, due to inbuilt resource and computing restriction, security in WSN needs a special consideration. Traditional security techniques such as encryption, VPN, authentication and firewalls cannot be directly applied to WSN as it provides defence only against external threats. The existing literature shows that there seems an inverse relationship between strong security mechanism and efficient network resource utilization. In this research article, we have proposed a Mobile Agent Based Hierarchical Intrusion Detection System (MABHIDS for WSN. The Proposed scheme performs two levels of intrusion detection by utilizing minimum possible network resources. Our proposed idea enhance network lifetime by reducing the work load on Cluster Head (CH and it also provide enhanced level of security in WSN.

  10. Using Conventional Monitoring Wells to Collect Data Necessary to Understand Petroleum Vapor Intrusion (PVI)

    Recent work has clearly established that the possibility for vapor intrusion of petroleum hydrocarbons is greatly reduced by aerobic biodegradation of the hydrocarbons in unsaturated soil. The rate and extent of aerobic biodegradation of benzene (or any other fuel hydrocarbon) in...

  11. Certification Considerations for Adaptive Systems

    Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

    2015-01-01

    Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

  12. A Survey to Scalable Distributed Intrusion Detection Methods%规模分布式网络入侵检测方法研究

    闫映松; 王志坚; 周晓峰

    2003-01-01

    With the rapid development of Internet,network security becomes more serious problem. Traditional technology can not meet the demand of scalable distributed network security ,and distributed intrusion detection architecture can solve the problems. However ,present intrusion detection systems still have many problems such as accuracy,reliability and adaptability. This paper discusses the present situation of intrusion detection and analyzes the problems that distributed intrusion detection exists and propose some technology and researches in point.

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

    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.

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

    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

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

    Puspendra Kumar

    2013-01-01

    Full Text Available 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 developed with the aid of java, php, dot net etc. In addition the proposed system detects directory traversal attacks, command injection attacks, cross site scripting attacks and SQL injection attacks, those were not detected in the existing IDS. This is an automatic technique for detection vulnerabilities over the internet. Our technique is based on the web application parameter which is in form of POST and GET which has generalized structure and values. This technique reduces analysis time of input validation attacks.

  16. Processing and Linguistics Properties of Adaptable Systems

    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].

  17. A New System for Clustering and Classification of Intrusion Detection System Alerts Using Self-Organizing Maps

    Amir Azimi Alasti Ahrabi, Ahmad Habibizad Navin, Hadi Bahrbegi, Mir Kamal Mirnia, Mehdi Bahrbegi, Elnaz Safarzadeh & Ali Ebrahimi

    2011-08-01

    Full Text Available Intrusion Detection Systems (IDS allow to protect systems used byorganizations against threats that emerges network connectivity by increasing.The main drawbacks of IDS are the number of alerts generated and failing. Byusing Self-Organizing Map (SOM, a system is proposed to be able to classifyIDS alerts and to reduce false positives alerts. Also some alert filtering andcluster merging algorithm are introduce to improve the accuracy of the proposedsystem. By the experimental results on DARPA KDD cup 98 the system is able tocluster and classify alerts and causes reducing false positive alerts considerably.

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

    Gomez-Carracedo, A.; Alvarez-Lorenzo, C.; Coca, R.; Martinez-Pacheco, R.; Concheiro, A. [Departamento de Farmacia y Tecnologia Farmaceutica, Universidad de Santiago de Compostela, Santiago de Compostela 15782 (Spain); Gomez-Amoza, J.L. [Departamento de Farmacia y Tecnologia Farmaceutica, Universidad de Santiago de Compostela, Santiago de Compostela 15782 (Spain)], E-mail: joseluis.gomez.amoza@usc.es

    2009-01-15

    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 {mu}m 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.

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

    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

  20. Towards a Cellular Automata Based Network Intrusion Detection System with Power Level Metric in Wireless Adhoc Networks (IDFADNWCA)

    Sree, Pokkuluri Kiran; Babu, Inampudi Ramesh

    2014-01-01

    Adhoc wireless network with their changing topology and distributed nature are more prone to intruders. The efficiency of an Intrusion detection system in the case of an adhoc network is not only determined by its dynamicity in monitoring but also in its flexibility in utilizing the available power in each of its nodes. In this paper we propose a hybrid intrusion detection system, based on a power level metric for potential adhoc hosts, which is used to determine the duration for which a part...

  1. Adaptive Behaviour Assessment System: Indigenous Australian Adaptation Model (ABAS: IAAM)

    du Plessis, Santie

    2015-01-01

    The study objectives were to develop, trial and evaluate a cross-cultural adaptation of the Adaptive Behavior Assessment System-Second Edition Teacher Form (ABAS-II TF) ages 5-21 for use with Indigenous Australian students ages 5-14. This study introduced a multiphase mixed-method design with semi-structured and informal interviews, school…

  2. Secured UAV based on multi-agent systems and embedded Intrusion Detection and Prevention Systems

    K.Boukhdir; F.Marzouk; H.MEDROMI; S.Tallal; S.Benhadou

    2015-01-01

    Unmanned aerial vehicles, or drones, are a relatively recent area of research and in full effervescence with more and more amateur and academic projects. Initially associated to the military, these vehicles are way to be used in many other areas. In effect, demand is growing for various applications within of this type of technology. Inspection of buildings, search and rescue of missing or in distress people are some examples. This research paper highlights a lightweight intrusion detectio...

  3. Cascading of C4.5 Decision Tree and Support Vector Machine for Rule Based Intrusion Detection System

    Jashan Koshal

    2012-08-01

    Full Text Available Main reason for the attack being introduced to the system is because of popularity of the internet. Information security has now become a vital subject. Hence, there is an immediate need to recognize and detect the attacks. Intrusion Detection is defined as a method of diagnosing the attack and the sign of malicious activity in a computer network by evaluating the system continuously. The software that performs such task can be defined as Intrusion Detection Systems (IDS. System developed with the individual algorithms like classification, neural networks, clustering etc. gives good detection rate and less false alarm rate. Recent studies show that the cascading of multiple algorithm yields much better performance than the system developed with the single algorithm. Intrusion detection systems that uses single algorithm, the accuracy and detection rate were not up to mark. Rise in the false alarm rate was also encountered. Cascading of algorithm is performed to solve this problem. This paper represents two hybrid algorithms for developing the intrusion detection system. C4.5 decision tree and Support Vector Machine (SVM are combined to maximize the accuracy, which is the advantage of C4.5 and diminish the wrong alarm rate which is the advantage of SVM. Results show the increase in the accuracy and detection rate and less false alarm rate.

  4. Towards Adaptive Spoken Dialog Systems

    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...

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

    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.

  6. An Active Host-Based Intrusion Detection System for ARP-Related Attacks and its Verification

    Ferdous A Barbhuiya

    2011-05-01

    Full Text Available Most of the LAN based-attacks involve the spoofing of the victim host with falsified IP-MAC pairs. MAC Spoofing is possible because of the state-less nature of the Address Resolution Protocol (ARP, which is responsible for resolving IP Addresses to MAC Addresses. Several mechanisms have been pro-posed to detect and mitigate ARP spoofing attempts both at the network level and at the host level, but each ofthem have their own drawback. In this paper we propose a Host-based Intrusion Detection system for LAN attacks which work without any extra constraint like static IP-MAC, modifying ARP etc. The scheme is successfully validated in a test bed with various attack scenarios and the results show the effectiveness of the proposed technique.

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

    Kang, Min-Joo

    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. PMID:27271802

  8. Geophysical detection of marine intrusions in Black Sea coastal areas (Romania) using VES and ERT data

    CHITEA, Florina; Georgescu, Paul; IOANE, Dumitru

    2011-01-01

    Abstract. Communities living in coastal areas depend in a great extent on the fresh water resources exploited from aquifers which are usually in a natural hydrodynamic equilibrium with the sea water. The contamination of fresh water with marine saltwater determines a significant increase in the aquifers electric conductivity, allowing an efficient application of resistivity methods in detecting and monitoring the marine intrusions. We present case studies from Romania (Costinesti and Vama Vec...

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

    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.

  10. Petrogenesis of postcollisional magmatism at Scheelite Dome, Yukon, Canada: Evidence for a lithospheric mantle source for magmas associated with intrusion-related gold systems

    Mair, John L.; Farmer, G. Lang; Groves, David I.; Hart, Craig J.R.; Goldfarb, Richard J.

    2011-01-01

    The type examples for the class of deposits termed intrusion-related gold systems occur in the Tombstone-Tungsten belt of Alaska and Yukon, on the eastern side of the Tintina gold province. In this part of the northern Cordillera, extensive mid-Cretaceous postcollisional plutonism took place following the accretion of exotic terranes to the continental margin. The most cratonward of the resulting plutonic belts comprises small isolated intrusive centers, with compositionally diverse, dominantly potassic rocks, as exemplified at Scheelite Dome, located in central Yukon. Similar to other spatially and temporally related intrusive centers, the Scheelite Dome intrusions are genetically associated with intrusion-related gold deposits. Intrusions have exceptional variability, ranging from volumetrically dominant clinopyroxene-bearing monzogranites, to calc-alkaline minettes and spessartites, with an intervening range of intermediate to felsic stocks and dikes, including leucominettes, quartz monzonites, quartz monzodiorites, and granodiorites. All rock types are potassic, are strongly enriched in LILEs and LREEs, and feature high LILE/HFSE ratios. Clinopyroxene is common to all rock types and ranges from salite in felsic rocks to high Mg augite and Cr-rich diopside in lamprophyres. Less common, calcic amphibole ranges from actinolitic hornblende to pargasite. The rocks have strongly radiogenic Sr (initial 87Sr/86Sr from 0.711-0.714) and Pb isotope ratios (206Pb/204Pb from 19.2-19.7), and negative initial εNd values (-8.06 to -11.26). Whole-rock major and trace element, radiogenic isotope, and mineralogical data suggest that the felsic to intermediate rocks were derived from mafic potassic magmas sourced from the lithospheric mantle via fractional crystallization and minor assimilation of metasedimentary crust. Mainly unmodified minettes and spessartites represent the most primitive and final phases emplaced. Metasomatic enrichments in the underlying lithospheric mantle

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

    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.

  12. Adapt

    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

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

    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

  14. Evaluation of the Effectiveness of Intrusion Detection System in a Nuclear Research Reactor

    The physical protection system of a nuclear facility is designed and implemented to prevent nuclear materials and nuclear facilities from illegal movement of nuclear materials or sabotage of nuclear facility. The effectiveness evaluation should be carried out in order to validate the performance of designed physical protection system. This work deals with the performance of a physical protection system of a nuclear research reactor to ensure that it meets the physical protection objectives. The effectiveness of the intrusion detection system is done by using a quantitative computer model. In this work only one path of an adversary who would plan to destroy a vital area in the research reactor is analyzed. The time values of detection, delay communication and response force action are measured along the adversary path. These values are used to calculate the probability of adversary interruption. The estimated output shows that the probability of intercepting the adversary would be before any sabotage is done. Also, the results show that the sufficient lighting system would improve the probability of detection system

  15. Novel Link Adaptation Schemes for OFDM System

    LEI Ming; CAI Peng; XU Yue-shan; ZHANG Ping

    2003-01-01

    Orthogonal Frequency Division Multiplexing (OFDM) is the most promising technique supporting the high data rate transmission. The combination of the link adaptation and OFDM can further increase the spectral efficiency. In this paper, we put forward two link adaptation schemes for OFDM system which have the advantages of both flexibility and practicability. Both of the two novel link adaptation schemes are based on the iterative mechanism to allocate the bit and power to subcarriers according to their channel gains and noisy levels which are assumed to be already known at the transmitter. The candidate modulation modes are determined freely before the link adaptation schemes are performed. The distinction between the two novel link adaptation schemes is that in the novel scheme A, the modulation mode is upgraded to the neighboring higher-order mode, while in the novel scheme B the modulation is upgraded to the genuine optimal mode. Therefore, the novel scheme A has the advantage of lower complexity and the novel scheme B has the advantage of higher spectral efficiency.

  16. Intrusion detection a machine learning approach

    Tsai, Jeffrey JP

    2011-01-01

    This important book introduces the concept of intrusion detection, discusses various approaches for intrusion detection systems (IDS), and presents the architecture and implementation of IDS. It emphasizes on the prediction and learning algorithms for intrusion detection and highlights techniques for intrusion detection of wired computer networks and wireless sensor networks. The performance comparison of various IDS via simulation will also be included.

  17. Semantic models for adaptive interactive systems

    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

  18. Framework of Combined Adaptive and Non-adaptive Attitude Control System for a Helicopter Experimental System

    Akira Inoue; Ming-Cong Deng

    2006-01-01

    This paper presents a framework of a combined adaptive and non-adaptive attitude control system for a helicopter experimental system. The design method is based on a combination of adaptive nonlinear control and non-adaptive nonlinear control. With regard to detailed attitude control system design, two schemes are shown for different application cases.

  19. Adaptive model training system and method

    Bickford, Randall L; Palnitkar, Rahul M; Lee, Vo

    2014-04-15

    An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

  20. Adaptive model training system and method

    Bickford, Randall L; Palnitkar, Rahul M

    2014-11-18

    An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

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

    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. PMID:26085452

  2. Adaptive embedded digital system for plasma diagnostics

    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.

  3. Architecture for Intrusion Detection System with Fault Tolerance Using Mobile Agent

    Chintan Bhatt; Asha Koshti; Hemant Agrawal; Zakiya Malek; Bhushan Trivedi

    2011-01-01

    This paper is a survey of the work, done for making an IDS fault tolerant.Architecture of IDS that usesmobile Agent provides higher scalability. Mobile Agent uses Platform for detecting Intrusions using filterAgent, co-relater agent, Interpreter agent and rule database. When server (IDS Monitor) goes down,other hosts based on priority takes Ownership. This architecture uses decentralized collection andanalysis for identifying Intrusion. Rule sets are fed based on user-behaviour or application...

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

    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

  5. Adaptive energy flow management in hybrid systems

    Drozdz, P.; Fitzpatrick, N.; Zettel, A.; Bouchon, N.; Inglis, A.; Strange, M. [Azure Dynamics Inc., Vancouver, BC (Canada)

    2000-07-01

    The use of adaptive energy management strategies for hybrid electric-powered vehicles was discussed with reference to the emission standards that must be met at the 100,000 mile point. The approach offers efficiency improvement and a cost reduction for simple series systems for medium duty vehicles. It also provides for improved battery management for parallel systems. The overall efficiency, durability and battery life in both series and parallel hybrid propulsion systems are strongly affected by the energy flow pattern between the primary energy source, battery and traction motor. The adaptive approach to energy management system aims for the dynamic optimisation of the system based on measured vehicle operating data. The approach uses computer tools to analyse driving patterns and to determine the most efficient control approach. It has a built-in learning ability to monitor the condition of the components and update the control strategy depending on the system's parameters. The system makes it possible to maintain maximum efficiency under any operating conditions while reducing the component load. The system was tested in a delivery vehicle and can successfully project fuel consumption. It was suggested that the method can be used to project greenhouse gas reduction figures for future fleets. refs., tabs., figs.

  6. FEATURES OF LOGISTIC SYSTEM ADAPTIVE MANAGEMENT

    Natalya VOZNENKO; Teodora ROMAN

    2015-01-01

    The study presents literature survey on enterprise logistic system adaptive management place and structure in the general enterprise management system. The theoretical basics of logistic system functioning, levels of its management and its effectiveness had been investigated. The role of adaptive management and its types had been scrutinized. The necessity of creating company’s adaptive regulator such as its economic mechanism had been proved.

  7. Adaptive feedback linearization of nonlinear SISO systems

    Gonzales, R. I.; Duarte-Mermoud, M. A.; Zagalak, Petr

    New Haven : Yale University, 2003, s. 160-169. [Workshop on Adaptive and Learning Systems /12./. Yale (US), 28.05.2003-30.05.2003] R&D Projects: GA ČR GA102/02/0204 Institutional research plan: CEZ:AV0Z1075907 Keywords : adaptive linearization * nonlinear systems * feedback linearization Subject RIV: BC - Control Systems Theory

  8. A Novel Broadband MIMO/OFDM System Using Adaptive Modulation and Adaptive Diversity

    PANYahan; KhaledBenLetaief; CAOZhigang; QIUYonghong

    2005-01-01

    OFDM (Orthogonal frequency division multiplexing) has been widely regarded as an effective modulation technique for mitigating the effects of ISI in a frequency selective fading channel and for providing reliable high-data transmission over wireless links. Adaptive modulation combined with adaptive transmit and receive diversity can achieve further increases in system's capacity and bandwidth efficiency, as well as in QoS improvement in conventional OFDM systems. In this paper, we propose a novel broadband MIMO/OFDM system using adaptive modulation and adaptive transmit and receive diversity. By applying an EVD on each sub-carrier channel matrix, joint optimal transmit and receive antenna weights as well as maximal SNR on each sub-carrier are obtained. Then, by employing adaptive modulation on each sub-carrier, the maximal SNR on each sub-carrier obtained by adaptive transmit and receive diversity is further maximized through adaptive bit assignment and power assignment on each sub-carrier under the constraint of power and overall bit rate. Simulation results show that the proposed system can achieve better performance than an adaptive antenna array based OFDM system without adaptive modulation over multipath fading channels.

  9. Non-Intrusive Electric Appliances Load Monitoring System-Experiment for Real Household-

    Murata, Hiroshi; Onoda, Takashi; Yoshimoto, Katsuhisa; Nakano, Yukio; Kondo, Syuhei

    This paper presents applying results of four estimation algorithms of non-intrusive monitoring system for real household. We conclude that all algorithms have practicable ability. 1) support vector machine(SVM): SVM was used to estimate ON/OFF states for fluorescent and refrigerator. SVM has the performance equivalent to best performance of sigmoid function networks(SFN). However, SVM has high estimating ability constantly. 2) RBF networks(RBFN): RBFN was used to estimate power consumption for air conditioner. RBFN has the performance equivalent to best performance of SFN. However, RBFN has high estimating ability constantly. 3) step change detection method(SCD): SCD was used to estimate ON/OFF states and power consumption for IH cooking range. SCD does not need the necessary learning process for SFN and has higher estimating ability than SFN. 4) spectrum reference method(SRM): SRM was used to estimate working conditions for rice cocker and washing machine. SRM is able to estimate these working conditions that cannot be estimated by earlier methods.

  10. Multi-pattern string matching algorithms comparison for intrusion detection system

    Hasan, Awsan A.; Rashid, Nur'Aini Abdul; Abdulrazzaq, Atheer A.

    2014-12-01

    Computer networks are developing exponentially and running at high speeds. With the increasing number of Internet users, computers have become the preferred target for complex attacks that require complex analyses to be detected. The Intrusion detection system (IDS) is created and turned into an important part of any modern network to protect the network from attacks. The IDS relies on string matching algorithms to identify network attacks, but these string matching algorithms consume a considerable amount of IDS processing time, thereby slows down the IDS performance. A new algorithm that can overcome the weakness of the IDS needs to be developed. Improving the multi-pattern matching algorithm ensure that an IDS can work properly and the limitations can be overcome. In this paper, we perform a comparison between our three multi-pattern matching algorithms; MP-KR, MPHQS and MPH-BMH with their corresponding original algorithms Kr, QS and BMH respectively. The experiments show that MPH-QS performs best among the proposed algorithms, followed by MPH-BMH, and MP-KR is the slowest. MPH-QS detects a large number of signature patterns in short time compared to other two algorithms. This finding can prove that the multi-pattern matching algorithms are more efficient in high-speed networks.

  11. Adapting bioinformatics curricula for big data

    Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S; Jason H Moore

    2015-01-01

    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...

  12. A kind of intrusion detection system of wireless Ad Hoc ethernet based on domain%一种基于域的无线Ad HOC网络入侵检测系统

    龚媛媛

    2012-01-01

    无线Ad Hoc网络因其高度动态的拓扑、无线链路、无固定基础设施的支持等一些特性使得它与其他网络相比是非常脆弱的.现有针对有线网络开发的IDS很难适用于这种网络.提出一种称为ZBIDS(Zone-Based Intrusion Detection System)的入侵检测系统,该系统采用两级层次化结构,属于分布式IDS.ZBIDS系统通过基于马尔可夫链的分类器来检测具有序列化特征的入侵.仿真结果表明,基于马尔可夫链的分类器具有较好的入侵检测性能.%Wireless Ad Hoc ethernet is comparatively vulnerable its characteristics such as dynamic topology, wireless connection and non-fixed foundation. The current IDS which are developed to suit network connection can' t adapt to the wireless one. This essay suggests the Zone-Based Intrusion Detection System (ZBIDS) which adopts two-stage hierarchical structure, belonging to distributive IDS. The ZBIDS can detect the ordered intrusion by the Markov chain classifier. The simulation results show that the Markov chain classifier can better detect the intrusion.

  13. Adaptive systems research in the NASA

    Montgomery, R.

    1973-01-01

    The past contributions of NASA to adaptive control technology are reviewed. The review places emphasis on aircraft applications although spacecraft and launch vehicle control applications are included. Particular emphasis is given to the adaptive control system used in the X-15 research aircraft. Problem areas that limited the realizable performance of this adaptive system are discussed. Current technological capabilities are used to extrapolate the present-day potential for adaptive flight control. Specifically, the potential created by use of the modern high-speed digital computer in flight control is discussed. Present plans for research in digital adaptive control systems for the NASA F8-C digital fly-by-wire program are presented. These plans are currently envisioned to include research in at least two types of adaptive controls, the system identification/on-line design type, and the model reference type.

  14. A Novel Intrusion Detection System for Wireless Body Area Network in Health Care Monitoring

    T. V.P. Sundararajan

    2010-01-01

    Full Text Available Problem statement: Health monitoring, telemedicine, military, interactive entertainment and portable audio/video systems were most promising applications where WBANs can be used. However, designers of such systems face a number of challenging tasks, as they need to address often quite conflicting requirements for size, operating time, precision and reliability. Network security is very important in Wireless Body Area Network (WBAN since the vital human life might be jeopardized, unless managed properly. Approach: This article presented security architecture of a wireless body area network for ambulatory health status monitoring. A novel Intrusion Detection System (IDS inspired by the biological immune system that use Negative Selection Algorithm (NSA was proposed to enhance the performance of Wireless Body Area Networks (WBAN to operate despite the presence of compromised (misbehaving nodes. Results: The proposed IDS scheme had been implemented using network simulator Qualnet v5.2. The performances of IDS scheme had been analyzed using AODV, DSR and DSDV routing protocols for parameters such as average detection rate and false alarm rate. These negative selection detectors are capable of distinguishing well behaving nodes from compromised nodes with good degree of accuracy. The high false positives rate is also minimized. Conclusion/Recommendations: Wireless Body Area Networks are an enabling technology for mobile health care. The IDS can be implemented on today’s devices as it only requires minimal and low-cost hardware changes. The authors strongly believe that adding sufficient security mechanisms to WBAN will study as a trigger in the acceptance of this technology for health care purposes. Simulation results indicate the non-degradability of network performance when these IDS is incorporated in the routing algorithm for security enhancements.

  15. Adaptive Control Applied to Financial Market Data

    Šindelář, Jan; Kárný, Miroslav

    Vol. I. Praha : Matfyz press, 2007, s. 1-6. ISBN 978-80-7378-023-4. [Week of Doctoral Students 2007. Praha (CZ), 05.06.2007-08.06.2007] R&D Projects: GA MŠk(CZ) 2C06001 Institutional research plan: CEZ:AV0Z10750506 Keywords : baysian statistics * finance * financial engineering * stochastic control Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2007/si/sindelar-adaptive control applied to financial market data.pdf

  16. Visualization of Scalar Adaptive Mesh Refinement Data

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

    2007-12-06

    Adaptive Mesh Refinement (AMR) is a highly effective computation method for simulations that span a large range of spatiotemporal scales, such as astrophysical simulations, which must accommodate ranges from interstellar to sub-planetary. Most mainstream visualization tools still lack support for AMR grids 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 scalar data visualization research.

  17. Model-Free Adaptive Control Algorithm with Data Dropout Compensation

    Xuhui Bu

    2012-01-01

    Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.

  18. Modeling Power Systems as Complex Adaptive Systems

    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.

  19. Adaptive passive equivalence of uncertain Lü system

    Qi Dong-Lian

    2006-01-01

    An adaptive passive strategy for controlling uncertain Lü system is proposed. Since the uncertain Lü system is minimum phase and the uncertain parameters are from a bounded compact set, the essential conditions are studied by which uncertain Lü system could be equivalent to a passive system, and the adaptive control law is given. Using passive theory, the uncertain Lü system could be globally asymptotically stabilized at different equilibria by the smooth state feedback.

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

    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.

  1. A fast ionised wind in a Star Forming-Quasar system at z~1.5 resolved through Adaptive Optics assisted near-infrared data

    Brusa, M; Cresci, G; Schramm, M; Delvecchio, I; Lanzuisi, G; Mainieri, V; Mignoli, M; Zamorani, G; Berta, S; Bongiorno, A; Comastri, A; Fiore, F; Kakkad, D; Marconi, A; Rosario, D; Contini, T; Lamareille, F

    2016-01-01

    Outflows are invoked in co-evolutionary models to link the growth of SMBH and galaxies through feedback phenomena, and from the analysis of both galaxies and Active Galactic Nuclei (AGN) samples at z$\\sim1-3$, it is becoming clear that powerful winds are quite common in AGN hosts. High-resolution and high S/N observations are needed in order to uncover the physical properties of the wind through kinematics analysis. We exploited VIMOS, SINFONI and Subaru/IRCS Adaptive Optics data to study the kinematics properties on the scale the host galaxy of XID5395, a luminous, X-ray obscured Starburst/Quasar merging system at z$\\sim1.5$ detected in the XMM-COSMOS field, and associated with an extreme [O II] emitter (EW$\\sim200$ \\AA). We mapped, for the first time, at high resolution the kinematics of the [O III] and H$\\alpha$ line complexes and linked them with the [O II] emission. The high spatial resolution achieved allowed us to resolve all the components of the SB-QSO system. Our analysis with a resolution of few kp...

  2. First steps in using machine learning on fMRI data to predict intrusive memories of traumatic film footage

    Clark, Ian A; Niehaus, Katherine E; Duff, Eugene P.; Di Simplicio, Martina C.; Clifford, Gari D.; Smith, Stephen M.; Mackay, Clare E.; Woolrich, Mark W.; Holmes, Emily A.

    2014-01-01

    After psychological trauma, why do some only some parts of the traumatic event return as intrusive memories while others do not? Intrusive memories are key to cognitive behavioural treatment for post-traumatic stress disorder, and an aetiological understanding is warranted. We present here analyses using multivariate pattern analysis (MVPA) and a machine learning classifier to investigate whether peri-traumatic brain activation was able to predict later intrusive memories (i.e. before they ha...

  3. Intelligent Multimodal Signal Adaptation System Project

    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...

  4. An Adaptive Multimodal Biometrics System using PSO

    Ola M. Aly; Tarek A. Mahmoud; Gouda I. Salama; Hoda M. Onsi

    2013-01-01

    Multimodal biometric systems which fuse information from a number of biometrics, are gaining more attentions lately because they are able to overcome limitations in unimodal biometric systems. These systems are suited for high security applications. Most of the proposed multibiometric systems offer one level of security. In this paper a new approach for adaptive combination of multiple biometrics has been proposed to ensure multiple levels of security. The score level fusion rule is adapted u...

  5. Adaptive information filtering for dynamic recommender systems

    Jin, Ci-Hang; Zhang, Yi-Cheng; Zhou, Tao

    2009-01-01

    The dynamic environment in the real world calls for the adaptive techniques for information filtering, namely to provide real-time responses to the changes of system data. Where many incremental algorithms are designed for this purpose, they are usually challenged by the worse and worse performance resulted from the cumulative errors over time. In this Letter, we propose two incremental diffusion-based algorithms for the personalized recommendations, which integrate some pieces of local and fast updatings to achieve the approximate results. In addition to the fast responses, the errors of the proposed algorithms do not cumulate over time, that is to say, the global recomputing is unnecessary. This remarkable advantage is demonstrated by several metrics on algorithmic accuracy for two movie recommender systems and a social bookmarking system.

  6. Web-Based Adaptive Testing System

    2006-01-01

    Due to the maturing of Internet technology, the adaptive testing can be utilized in the web-based environment and the examinee can take the test anywhere and any time. The purpose of the research is to apply item response theory (IRT), adaptive testing theory and web-service technique to construct an XML format itembank and a system of web-based adaptive testing (WAT) by the framework of three-tiered client server distance testing.

  7. Intrusion Detection and Countermeasure of Virtual Cloud Systems - State of the Art and Current Challenges

    Andrew Carlin

    2015-06-01

    Full Text Available Clouds are distributed Internet-based platforms that provide highly resilient and scalable environments to be used by enterprises in a multitude of ways. Cloud computing offers enterprises technology innovation that business leaders and IT infrastructure managers can choose to apply based on how and to what extent it helps them fulfil their business requirements. It is crucial that all technical consultants have a rigorous understanding of the ramifications of cloud computing as its influence is likely to spread the complete IT landscape. Security is one of the major concerns that is of practical interest to decision makers when they are making critical strategic operational decisions. Distributed Denial of Service (DDoS attacks are becoming more frequent and effective over the past few years, since the widely publicised DDoS attacks on the financial services industry that came to light in September and October 2012 and resurfaced in the past two years. In this paper, we introduce advanced cloud security technologies and practices as a series of concepts and technology architectures, from an industry-centric point of view. This is followed by classification of intrusion detection and prevention mechanisms that can be part of an overall strategy to help understand, identify and mitigate potential DDoS attacks on business networks. The paper establishes solid coverage of security issues related to DDoS and virtualisation with a focus on structure, clarity, and well-defined blocks for mainstream cloud computing security solutions and platforms. In doing so, we aim to provide industry technologists, who may not be necessarily cloud or security experts, with an effective tool to help them understand the security implications associated with cloud adoption in their transition towards more knowledge-based systems.

  8. Progressive Prediction of Turbulence Using Wave-Front Sensor Data in Adaptive Optics Using Data Mining

    Vyas, Akondi; Roopashree, M. B.; Prasad, B Raghavendra

    2009-01-01

    Nullifying the servo bandwidth errors improves the strehl ratio by a substantial quantity in adaptive optics systems. An effective method for predicting atmospheric turbulence to reduce servo bandwidth errors in real time closed loop correction systems is presented using data mining. Temporally evolving phase screens are simulated using Kolmogorov statistics and used for data analysis. A data cube is formed out of the simulated time series. Partial data is used to predict the subsequent phase...

  9. Adaptive Partitioning for Very Large RDF Data

    Harbi, Razen; Abdelaziz, Ibrahim; Kalnis, Panos; Mamoulis, Nikos; Ebrahim, Yasser; Sahli, Majed

    2015-01-01

    Distributed RDF systems partition data across multiple computer nodes (workers). Some systems perform cheap hash partitioning, which may result in expensive query evaluation, while others apply heuristics aiming at minimizing inter-node communication during query evaluation. This requires an expensive data preprocessing phase, leading to high startup costs for very large RDF knowledge bases. Apriori knowledge of the query workload has also been used to create partitions, which however are sta...

  10. An adaptive association test for microbiome data.

    Wu, Chong; Chen, Jun; Kim, Junghi; Pan, Wei

    2016-01-01

    There is increasing interest in investigating how the compositions of microbial communities are associated with human health and disease. Although existing methods have identified many associations, a proper choice of a phylogenetic distance is critical for the power of these methods. To assess an overall association between the composition of a microbial community and an outcome of interest, we present a novel multivariate testing method called aMiSPU, that is joint and highly adaptive over all observed taxa and thus high powered across various scenarios, alleviating the issue with the choice of a phylogenetic distance. Our simulations and real-data analyses demonstrated that the aMiSPU test was often more powerful than several competing methods while correctly controlling type I error rates. The R package MiSPU is available at https://github.com/ChongWu-Biostat/MiSPU and CRAN. PMID:27198579

  11. Meeting Ecologists Requirements with Adaptive Data Acquisition

    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 p...

  12. ADAPTIVE REGULATION OF HIGH ORDER NONHOLONOMIC SYSTEMS

    2006-01-01

    The problem of adaptive regulation of a class of high-order parametric nonholonomic systems in chained-form was discussed. Using adding a power integrator technique and state scaling with discontinuous projection technique, a discontinuous adaptive dynamic controller was constructed. The controller guarantees the estimated value of unknown parameter is in the prescribed extent.

  13. Development of operational system for monitoring and studying groundwater discharge and seawater intrusion in coastal zones

    One of the important challenges facing coastal zone managers today is how to identify, measure and monitor coastal submarine groundwater discharge (SGD) and seawater intrusion (SWI) and how to evaluate its influence on cumulative impacts of coastal land use decisions over distance and time. Several geochemical and geophysical techniques can help to solve the problem and provide direct or indirect monitoring of saltwater in coastal aquifers. We report here the results of a three dimensional (3D) geoelectrical survey carried out near the harbour in Donnalucata along the southeastern coast of Sicily. A geoelectrical survey and geo-mapping of the spatial distribution of the saltwater-freshwater interface in the coastal zone was conducted during the IAEA- SGD experiment in Sicily (IAEA SGD CRP 2001-2006). The Transient Electromagnetic Method (TEM) allows a subsurface sounding up to 300 m deep. This study shows the presence of two layers with various types of salt mineralization of subsurface waters in the coastal zone of Donnalucata. Geoelectrical data were taken for two subsurface layers with different types of subsurface water: resistivity = 5.37 Ω. m and with mineralization of the groundwater between 2000 - 2500 mg/L (basic water-saturated horizon from 5 to 15 m deep), and a second zone (depths from 50 to 70 m deep) with resistivity = 3.32 Ω. m and mineralization of groundwater between 4500 - 5000 mg/L. Analysis of the geoelectrical data has shown that there is a zone of maximum discharge located in the channel between two piers of the harbour. This maximum discharge reflects the existence of a known specific local karstic groundwater phenomena off the coastal zone of Donnalucata, which was confirmed with the method presented here. The geoelectromagnetic data confirmed the observations made by seepage meters and in situ measurements of 222Rn concentration and salinity, which showed at some places high seepage rates of recirculated seawater. Although overuse and

  14. An immune based dynamic intrusion detection model

    LI Tao

    2005-01-01

    With the dynamic description method for self and antigen, and the concept of dynamic immune tolerance for lymphocytes in network-security domain presented in this paper, a new immune based dynamic intrusion detection model (Idid) is proposed. In Idid, the dynamic models and the corresponding recursive equations of the lifecycle of mature lymphocytes, and the immune memory are built. Therefore, the problem of the dynamic description of self and nonself in computer immune systems is solved, and the defect of the low efficiency of mature lymphocyte generating in traditional computer immune systems is overcome. Simulations of this model are performed, and the comparison experiment results show that the proposed dynamic intrusion detection model has a better adaptability than the traditional methods.

  15. Geochemical and isotopic data for restricting seawater intrusion and groundwater circulation in a series of typical volcanic islands in the South China Sea

    Highlights: • Seawater intrusion was reported in northeastern coast of South China Sea for the first time. • Seawater intrusion have resulted in significant groundwater salinization. • Unique intrusion pattern in volcanic islands have been observed. • Existence of isolated palaeowater was demonstrated. - Abstract: The decline of groundwater table and deterioration of water quality related to seawater have long been regarded as a crucial problem in coastal regions. In this work, a hydrogeologic investigation using combined hydrochemical and isotopic approaches was conducted in the coastal region of the South China Sea near the Leizhou peninsular to provide primary insight into seawater intrusion and groundwater circulation. Hydrochemical and isotopic data show that local groundwater is subjected to anthropogenic activities and geochemical processes, such as evaporation, water–rock interaction, and ion exchange. However, seawater intrusion driven by the over-exploitation of groundwater and insufficient recharge is the predominant factor controlling groundwater salinization. Systematic and homologic isotopic characteristics of most samples suggest that groundwater in volcanic area is locally recharged and likely caused by modern precipitation. However, very depleted stable isotopes and extremely low tritium of groundwater in some isolated aquifers imply a dominant role of palaeowater

  16. Dynamic data-driven sensor network adaptation for border control

    Bein, Doina; Madan, Bharat B.; Phoha, Shashi; Rajtmajer, Sarah; Rish, Anna

    2013-06-01

    Given a specific scenario for the border control problem, we propose a dynamic data-driven adaptation of the associated sensor network via embedded software agents which make sensor network control, adaptation and collaboration decisions based on the contextual information value of competing data provided by different multi-modal sensors. We further propose the use of influence diagrams to guide data-driven decision making in selecting the appropriate action or course of actions which maximize a given utility function by designing a sensor embedded software agent that uses an influence diagram to make decisions about whether to engage or not engage higher level sensors for accurately detecting human presence in the region. The overarching goal of the sensor system is to increase the probability of target detection and classification and reduce the rate of false alarms. The proposed decision support software agent is validated experimentally on a laboratory testbed for multiple border control scenarios.

  17. Managing software complexity of adaptive systems

    Roo, de Auke Jan

    2012-01-01

    To survive under competitive pressure, embedded system companies build systems that can deal with changing customer needs and operating conditions, and deterioration of the hardware over the lifetime of the embedded system. Engineers face the challenge to design such adaptive systems, while keeping

  18. A FEATURE SELECTION ALGORITHM DESIGN AND ITS IMPLEMENTATION IN INTRUSION DETECTION SYSTEM

    杨向荣; 沈钧毅

    2003-01-01

    Objective Present a new features selection algorithm. Methods based on rule induction and field knowledge. Results This algorithm can be applied in catching dataflow when detecting network intrusions, only the sub-dataset including discriminating features is catched. Then the time spend in following behavior patterns mining is reduced and the patterns mined are more precise. Conclusion The experiment results show that the feature subset catched by this algorithm is more informative and the dataset's quantity is reduced significantly.

  19. Fuzzy adaptive synchronization of uncertain chaotic systems

    This Letter presents an adaptive approach for synchronization of Takagi-Sugeno (T-S) fuzzy chaotic systems. Since the parameters of chaotic system are assumed unknown, the adaptive law is derived to estimate the unknown parameters and its stability is guaranteed by Lyapunov stability theory. The control law to be designed consists of two parts: one part that can stabilize the synchronization error dynamics and the other part that estimates the unknown parameters. Numerical examples are given to demonstrate the validity of the proposed adaptive synchronization approach

  20. CRISPR adaptive immune systems of Archaea

    Vestergaard, Gisle; Garrett, Roger A.; Shah, Shiraz A.

    2014-01-01

    CRISPR adaptive immune systems were analyzed for all available completed genomes of archaea, which included representatives of each of the main archaeal phyla. Initially, all proteins encoded within, and proximal to, CRISPR-cas loci were clustered and analyzed using a profile–profile approach. Then cas genes were assigned to gene cassettes and to functional modules for adaptation and interference. CRISPR systems were then classified primarily on the basis of their concatenated Cas protein seq...

  1. ADAPTIVE GENERALIZED PREDICTIVE CONTROL OF SWITCHED SYSTEMS

    WANG Yi-jing; WANG Long

    2005-01-01

    The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied. The switching law is determined by the output predictive errors of a finite number of subsystems. For the single subsystem and multiple subsystems cases, it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system. This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.

  2. Zircon Recycling in Arc Intrusions

    Miller, J.; Barth, A.; Matzel, J.; Wooden, J.; Burgess, S.

    2008-12-01

    Recycling of zircon has been well established in arc intrusions and arc volcanoes, but a better understanding of where and how zircons are recycled can help illuminate how arc magma systems are constructed. To that end, we are conducting age, trace element (including Ti-in-zircon temperatures; TzrnTi) and isotopic studies of zircons from the Late Cretaceous (95-85 Ma) Tuolumne Intrusive Suite (TIS) in the Sierra Nevada Batholith (CA). Within the TIS zircons inherited from ancient basement sources and/or distinctly older host rocks are uncommon, but recycled zircon antecrysts from earlier periods of TIS-related magmatism are common and conspicuous in the inner and two most voluminous units of the TIS, the Half Dome and Cathedral Peak Granodiorites. All TIS units have low bulk Zr ([Zr]825°C), [Zr] in the TIS is a factor of 2 to 3 lower than saturation values. Low [Zr] in TIS rocks might be attributed to a very limited supply of zircon in the source, by disequilibrium melting and rapid melt extraction [1], by melting reactions involving formation of other phases that can incorporate appreciable Zr [2], or by removal of zircon at an earlier stage of magma evolution. Based on a preliminary compilation of literature data, low [Zr] is common to Late Cretaceous N.A. Cordilleran granodioritic/tonalitic intrusions (typically Tzrnsat [3]. A corollary is that slightly older zircon antecrysts that are common in the inner units of the TIS could be considered inherited if they are derived from remelting of slightly older intrusions. Remelting at such low temperatures in the arc would require a source of external water. Refs: [1] Sawyer, J.Pet 32:701-738; [2] Fraser et al, Geology 25:607-610; [3] Harrison et al, Geology 35:635- 638

  3. A fast ionised wind in a star-forming quasar system at z ~ 1.5 resolved through adaptive optics assisted near-infrared data

    Brusa, M.; Perna, M.; Cresci, G.; Schramm, M.; Delvecchio, I.; Lanzuisi, G.; Mainieri, V.; Mignoli, M.; Zamorani, G.; Berta, S.; Bongiorno, A.; Comastri, A.; Fiore, F.; Kakkad, D.; Marconi, A.; Rosario, D.; Contini, T.; Lamareille, F.

    2016-04-01

    Aims: Outflow winds are invoked in co-evolutionary models to link the growth of SMBH and galaxies through feedback phenomena, and from the analysis of both galaxies and active galactic nuclei (AGN) samples at z ~ 1-3, it is becoming clear that powerful outflows may be very common in AGN hosts. High-resolution and high S/N observations are needed to uncover the physical properties of the wind through kinematics analysis. Methods: We exploited VLT/VIMOS, VLT/SINFONI, and Subaru/IRCS adaptive optics (AO) data to study the kinematics properties on the scale of the host galaxy of XID5395; this galaxy is a luminous, X-ray obscured starburst/quasar (SB-QSO) merging system at z ~ 1.5, detected in the XMM-COSMOS field, associated with an extreme [O II] emitter (with equivalent width, EW, ~200 Å). For the first time, we mapped the kinematics of the [O III] and Hα line complexes and linked them with the [O II] emission at high resolution. The high spatial resolution achieved allowed us to resolve all the components of the SB-QSO system. Results: Our analysis, with a resolution of few kpc, reveals complexities and asymmetries in and around the nucleus of XID5395. The velocity field measured via non-parametric analysis reveals different kinematic components with maximum blueshifted and redshifted velocities up to ≳ 1300 km s-1 that are not spatially coincident with the nuclear core. These extreme values of the observed velocities and spatial location can be explained by the presence of fast moving material. We also spectroscopically confirm the presence of a merging system at the same redshift as the AGN host. Conclusions: We propose that EW as large as >150 Å in X-ray selected AGN may be an efficient criterion to isolate objects associated with the short, transition phase of "feedback" in the AGN-galaxy co-evolutionary path. This co-evolutionary path subsequently evolves into an unobscured QSO, as suggested from the different observational evidence (e.g. merger, compact

  4. Adaptive Dialogue Systems for Assistive Living Environments

    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…

  5. Complex and adaptive dynamical systems a primer

    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...

  6. Complex and Adaptive Dynamical Systems A Primer

    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...

  7. GLIMPCE Seismic reflection evidence of deep-crustal and upper-mantle intrusions and magmatic underplating associated with the Midcontinent Rift system of North America

    Behrendt, J. C.; Hutchinson, D. R.; Lee, M.; Thornber, C. R.; Tréhu, A.; Cannon, W.; Green, A.

    1990-02-01

    Deep-crustal and Moho reflections, recorded on vertical incidence and wide angle ocean bottom Seismometer (OBS) data in the 1986 GLIMPCE (Great Lakes International Multidisciplinary Program on Crustal Evolution) experiment, provide evidence for magmatic underplating and intrusions within the lower crust and upper mantle contemporaneous with crustal extension in the Midcontinent Rift system at 1100 Ma. The rift fill consists of 20-30 km (7-10 s) of basalt flows, secondary syn-rift volcaniclastic and post-basalt sedimentary rock. Moho reflections recorded in Lake Superior over the Midcontinent Rift system have times from 14-18 s (about 46 km to as great as 58 km) in contrast to times of about 11-13 s (about 36-42 km crustal thickness) beneath the surrounding Great Lakes. The Seismically complex deep-crust to mantle transition zone (30-60 km) in north-central Lake Superior, which is 100 km wider than the rift half-graben, reflects the complicated products of tectonic and magmatic interaction of lower-crustal and mantle components during evolution or shutdown of the aborted Midcontinent Rift. In effect, mantle was changed into crust by lowering Seismic velocity (through intrusion of lower density magmatic rocks) and increasing Moho (about 8.1 km s-1 depth.

  8. Resonant blade response in turbine rotor spin tests using a laser-light probe non-intrusive measurement system

    Mansisidor, Michael R.

    2002-01-01

    Procedures to qualify turbo-machinery components for a designed lifetime free of high cycle fatigue (HCF) failures have not yet evolved. As part of an initiative to address this issue, in the present study, laser-light probes were used in a Non- Intrusive Measurement System (NSMS) to measure the unsteady deflections created in the blades of a second-stage turbine rotor in an evacuated spin pit. Air-jet and eddy-current excitation (ECE) methods were used to stimulate blade resonance. The NSMS ...

  9. High temperature metamorphism in the conductive boundary layer adjacent to a rhyolite intrusion in the Krafla geothermal system, Iceland

    P. Schiffman; Zierenberg, RA; Mortensen, AK; Frioleifsson, GO; Elders, WA

    2014-01-01

    A rhyolite magma body within the Krafla geothermal system that was encountered at a depth of 2.1km during drilling of the IDDP-1 borehole is producing high temperature metamorphism within a conductive boundary layer (CBL) in adjacent host rocks. Cuttings recovered during drilling within a few meters of the intrusive contact in IDDP-1 are mainly comprised of granoblastic hornfelses, the rock type which confirms the presence of the CBL at the base of the IDDP-1 bore hole. The two pyroxenes in t...

  10. Quantitative Adaptation Analytics for Assessing Dynamic Systems of Systems.

    Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.; Le, Hai D.; Kao, Gio K; Melander, Darryl J.; Longsine, Dennis Earl [Sandia National Laboratories, Unknown, Unknown; Vander Meer, Robert Charles,

    2015-01-01

    Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combining the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.

  11. Efficient Hybrid Network (Wired and Wireless) Intrusion Detection using Statistical Data Streams and Detection of Clustered Alerts

    Thangavel, M.; Thangaraj, P.

    2011-01-01

    Problem statement: Wireless LAN IEEE 802.11 protocols are growing rapidly and security has always been a concern with the security of wired network. Wireless networks encountered threats from unauthorized access to network resources, installation of access points and illegal sniffing (refer as classical intrusion threats). In its current hybrid wired and wireless network attacks on the generally distinguish from normal cable intrusion attacks, selective forwarding attacks, MAC spoofing attack...

  12. First steps in using machine learning on fMRI data to predict intrusive memories of traumatic film footage.

    Clark, Ian A; Niehaus, Katherine E; Duff, Eugene P; Di Simplicio, Martina C; Clifford, Gari D; Smith, Stephen M; Mackay, Clare E; Woolrich, Mark W; Holmes, Emily A

    2014-11-01

    After psychological trauma, why do some only some parts of the traumatic event return as intrusive memories while others do not? Intrusive memories are key to cognitive behavioural treatment for post-traumatic stress disorder, and an aetiological understanding is warranted. We present here analyses using multivariate pattern analysis (MVPA) and a machine learning classifier to investigate whether peri-traumatic brain activation was able to predict later intrusive memories (i.e. before they had happened). To provide a methodological basis for understanding the context of the current results, we first show how functional magnetic resonance imaging (fMRI) during an experimental analogue of trauma (a trauma film) via a prospective event-related design was able to capture an individual's later intrusive memories. Results showed widespread increases in brain activation at encoding when viewing a scene in the scanner that would later return as an intrusive memory in the real world. These fMRI results were replicated in a second study. While traditional mass univariate regression analysis highlighted an association between brain processing and symptomatology, this is not the same as prediction. Using MVPA and a machine learning classifier, it was possible to predict later intrusive memories across participants with 68% accuracy, and within a participant with 97% accuracy; i.e. the classifier could identify out of multiple scenes those that would later return as an intrusive memory. We also report here brain networks key in intrusive memory prediction. MVPA opens the possibility of decoding brain activity to reconstruct idiosyncratic cognitive events with relevance to understanding and predicting mental health symptoms. PMID:25151915

  13. Adaptation in the auditory system: an overview

    David ePérez-González; Malmierca, Manuel S.

    2014-01-01

    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 s...

  14. StreamingBandit: Developing Adaptive Persuasive Systems

    Kaptein, Maurits; Kruijswijk, Jules

    2016-01-01

    This paper introduces StreamingBandit, a (back-end) solution for developing adaptive and personalized persuasive systems. Creating successful persuasive applications requires a combination of design, social science, and technology. StreamingBandit contributes to the required technology by providing a platform that can be used to adapt persuasive technologies in real-time and at large scales. We first introduce the design philosophy of StreamingBandit using a running example and highlight how ...

  15. Slow Adaptive OFDMA Systems ThroughChance Constrained Programming

    N. Revathy

    2012-03-01

    Full Text Available Abstract—Adaptive orthogonal frequency division multiple Access (OFDMA has recently been recognized as a promising Technique for providing high spectral efficiency in future broadband Wireless systems. The research over the last decade on Adaptive OFDMA systems has focused on adapting the allocation Of radio resources, such as sub carriers and power, to the instantaneous Channel conditions of all users. However, such “fast” adaptation requires high computational complexity and excessive signalling overhead. This hinders the deployment of adaptive OFDMA systems worldwide. This paper proposes a slow adaptive OFDMA scheme, in which the sub carrier allocation is updated on a much slower timescale than that of the fluctuation of instantaneous channel conditions. Meanwhile, the data rate requirements of individual users are accommodated on the fast timescale with high probability, thereby meeting the requirements except occasional outage. Such an objective has a natural chance constrained programming formulation, which is known to be intractable. To circumvent this difficulty, we formulate safe tractable constraints or the problem based on recent advances in chance constrained programming. We then develop a polynomial-time algorithm for computing an optimal solution to the reformulated problem. Our results show that the proposed slow adaptation scheme drastically reduces both computational cost and control signalling overhead when compared with the conventional fast adaptive OFDMA.

  16. Preliminary images from an adaptive imaging system.

    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; Ostby, J M; Psomadellis, F; van der Stelt, P F; Theodoridis, S; Triantis, F; Turchetta, R; Venanzi, C; Speller, R D

    2008-06-01

    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 cephalography. In our system, the exposure in each image region is optimised and the beam intensity is a function of tissue thickness and attenuation, and also of local physical and statistical parameters in the image. Using a linear array of detectors, the system will perform on-line analysis of the image during the scan, followed by optimisation of the X-ray intensity to obtain the maximum diagnostic information from the region of interest while minimising exposure of diagnostically less important regions. This paper presents preliminary images obtained with a small area CMOS detector developed for this application. Wedge systems were used to modulate the beam intensity during breast and dental imaging using suitable X-ray spectra. The sensitive imaging area of the sensor is 512 x 32 pixels 32 x 32 microm(2) in size. The sensors' X-ray sensitivity was increased by coupling to a structured CsI(Tl) scintillator. In order to develop the I-ImaS prototype, the on-line data analysis and data acquisition control are based on custom-developed electronics using multiple FPGAs. Images of both breast tissues and jaw samples were acquired and different exposure optimisation algorithms applied. Results are very promising since the average dose has been reduced to around 60% of the dose delivered by conventional imaging systems without decrease in the visibility of details. PMID:18291697

  17. Adaptive data management in the ARC Grid middleware

    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.

  18. Development and Simulation of Early-Warning and Predicting System for Saltwater Intrusion%咸潮入侵预警预报信息系统的设计与仿真

    沈萍萍; 方立刚

    2011-01-01

    The online warning and forecasting of saltwater intrusion are studied. Currently, saltwater intrusion model can only display the measured data, and the timely warning and forecast can not be achieved. To solve the above problem, this paper presents a variable estuarine salinity simulation model, and gives the iterative algorithm of early warning. As long as accessing parameters, such as estuarine salinity and runoff etc. , accurate early warning of the salinity of local saltwater intrusion and the largest local saltwater intrusion distance can be rapidly realized, which solves the technical problems of local saltwater intrusion forecasting. Experimental results show that the propesed simulation iteration variable salinity estuary warning algorithm has relatively low error, and can accurately monitor saltwater intrusion. The saltwater intrusion forecasting information system developed basedon the algorithm has visual online early warning pattern. Using this system, the early-warning of saltwater intrusion can be electronized.%研究咸潮入侵实时、准确预警预报问题.目前咸潮入侵多为实测数据,没有相应的预警预报系统,无法实时、准确地预警咸情.为解决上述问题,提出可变河口盐度仿真迭代预警模型并给出实现算法.只要获取河口盐度和径流量等几个参数就能快速准确预警当地咸潮入侵盐度和入侵距离,解决了当地咸潮入侵预警预报实时性和准确性的技术难题.经过仿真证明.可变河口盐度模拟迭代预警算法误差较小,能快速、准确地监测预警咸潮入侵情况;基于算法开发设计的咸潮入侵预警预报信息系统在线预警形式直观,实现了珠三角地区成情的实时、准确预警,证明了预报系统的有效性.

  19. Adaptive multiscale entropy analysis of multivariate neural data.

    Hu, Meng; Liang, Hualou

    2012-01-01

    Multiscale entropy (MSE) has been widely used to quantify a system's complexity by taking into account the multiple time scales inherent in physiologic time series. The method, however, is biased toward the coarse scale, i.e., low-frequency components due to the progressive smoothing operations. In addition, the algorithm for extracting the different scales is not well adapted to nonlinear/nonstationary signals. In this letter, we introduce adaptive multiscale entropy (AME) measures in which the scales are adaptively derived directly from the data by virtue of recently developed multivariate empirical mode decomposition. Depending on the consecutive removal of low-frequency or high-frequency components, our AME can be estimated at either coarse-to-fine or fine-to-coarse scales over which the sample entropy is performed. Computer simulations are performed to verify the effectiveness of AME for analysis of the highly nonstationary data. Local field potentials collected from the visual cortex of macaque monkey while performing a generalized flash suppression task are used as an example to demonstrate the usefulness of our AME approach to reveal the underlying dynamics in complex neural data. PMID:21788182

  20. Preliminary images from an adaptive imaging system

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

    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 cephal

  1. 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

    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.

  2. Adaptation in the auditory system: an overview

    David Pérez-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.

  3. An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor Networks

    Byoung-Jin Bae; Young-Joo Kim; Young-Kuk Kim; Ok-Kyoon Ha; Yong-Kee Jun

    2014-01-01

    Owing to the acceleration of IoT- (Internet of Things-) based wireless sensor networks, cloud-computing services using Big Data are rapidly growing. In order to manage and analyze Big Data efficiently, Hadoop frameworks have been used in a variety of fields. Hadoop processes Big Data as record values by using MapReduce programming in a distributed environment. Through MapReduce, data are stored in a Hadoop file system, and that form is not structured but unstructured. For this, it is not easy...

  4. Electric vehicle data acquisition system

    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. The New Trends in Adaptive Educational Hypermedia Systems

    Sibel Somyürek

    2015-02-01

    Full Text Available This paper aims to give a general review of existing literature on adaptive educational hypermedia systems and to reveal technological trends and approaches within these studies. Fifty-six studies conducted between 2002 and 2012 were examined, to identify prominent themes and approaches. According to the content analysis, the new technological trends and approaches were grouped into seven categories: standardization, semantic web, modular frameworks, data mining, machine learning techniques, social web, and device adaptation. Furthermore, four challenges are suggested as explanation why adaptive systems are still not used on a large scale: inter-operability, open corpus knowledge, usage across a variety of delivery devices, and the design of meta-adaptive systems.

  6. The ERIS Adaptive Optics System

    Riccardi, A; Agapito, G; Antichi, J; Biliotti, V; Blain, C; Briguglio, R; Busoni, L; Carbonaro, L; Di Rico, G; Giordano, C; Pinna, E; Puglisi, A; Spanò, P; Xompero, M; Baruffolo, A; Kasper, M; Egner, S; Valles, M Suàrez; Soenke, C; Downing, M; Reyes, J

    2016-01-01

    ERIS is the new AO instrument for VLT-UT4 led by a Consortium of Max-Planck Institut fuer Extraterrestrische Physik, UK-ATC, ETH-Zurich, ESO and INAF. The ERIS AO system provides NGS mode to deliver high contrast correction and LGS mode to extend high Strehl performance to large sky coverage. The AO module includes NGS and LGS wavefront sensors and, with VLT-AOF Deformable Secondary Mirror and Laser Facility, will provide AO correction to the high resolution imager NIX (1-5um) and the IFU spectrograph SPIFFIER (1-2.5um). In this paper we present the preliminary design of the ERIS AO system and the estimated correction performance.

  7. On Capability-Related Adaptation in Networked Service Systems

    Finn Arve Aagesen; Patcharee Thongtra

    2012-01-01

    Adaptability is a property related to engineering as well as to the execution of networked service systems. This publication considers issues of adaptability both within a general and a scoped view. The generalview considers issues of adaptation at two levels: 1) System of entities, functions and adaptability types, and 2) Architectures supporting adaptability. Adaptability types defined are capability-related, functionality-related and context-related adaptation. The scoped view of the publi...

  8. Adaptive control of solar energy collector systems

    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

  9. Evolving Systems and Adaptive Key Component Control

    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.

  10. Environmentally-adapted local energy systems

    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.

  11. An Adaptive Multimodal Biometrics System using PSO

    Ola M. Aly

    2013-08-01

    Full Text Available Multimodal biometric systems which fuse information from a number of biometrics, are gaining more attentions lately because they are able to overcome limitations in unimodal biometric systems. These systems are suited for high security applications. Most of the proposed multibiometric systems offer one level of security. In this paper a new approach for adaptive combination of multiple biometrics has been proposed to ensure multiple levels of security. The score level fusion rule is adapted using (PSO Particle Swarm Optimization to ensure the desired system performance corresponding to the desired level of security. The experimental results prove that the proposed multimodal biometric system is appropriate for applications that require different levels of security.

  12. An Agent Based Intrusion Detection Model for Mobile Ad Hoc Networks

    B. M. Reshmi

    2006-01-01

    Full Text Available Intrusion detection has over the last few years, assumed paramount importance within the broad realm of network security, more so in case of wireless mobile ad hoc networks. The inherently vulnerable characteristics of wireless mobile ad hoc networks make them susceptible to attacks in-spite of some security measures, and it may be too late before any counter action can take effect. As such, there is a need to complement traditional security mechanisms with efficient intrusion detection and response systems. This paper proposes an agent-based model to address the aspect of intrusion detection in cluster based mobile wireless ad hoc network environment. The model comprises of a set of static and mobile agents, which are used to detect intrusions, respond to intrusions, and distribute selected and aggregated intrusion information to all other nodes in the network in an intelligent manner. The model is simulated to test its operation effectiveness by considering the performance parameters such as, detection rate, false positives, agent overheads, and intrusion information distribution time. Agent based approach facilitates flexible and adaptable security services. Also, it supports component based software engineering components such as maintainability, reachability, reusability, adaptability, flexibility, and customization.

  13. SATZ An Adaptive Sentence Segmentation System

    Palmer, D D

    1995-01-01

    This paper provides a detailed description of the sentence segmentation system first introduced in cmp-lg/9411022. It provides results of systematic experiments involving sentence boundary determination, including context size, lexicon size, and single-case texts. Also included are the results of successfully adapting the system to German and French. The source code for the system is available as a compressed tar file at ftp://cs-tr.CS.Berkeley.EDU/pub/cstr/satz.tar.Z .

  14. Data Systems vs. Information Systems

    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.

  15. Final Report - Regulatory Considerations for Adaptive Systems

    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.

  16. DESIGN PATTERNS FOR SELF ADAPTIVE SYSTEMS ENGINEERING

    Yousef Abuseta

    2015-07-01

    Full Text Available Self adaptation has been proposed to overcome the complexity of today's software systems which results from the uncertainty issue. Aspects of uncertainty include changing systems goals, changing resource availability and dynamic operating conditions. Feedback control loops have been recognized as vital elements for engineering self-adaptive systems. However, despite their importance, there is still a lack of systematic way of the design of the interactions between the different components comprising one particular feedback control loop as well as the interactions between components from different control loops . Most existing approaches are either domain specific or too abstract to be useful. In addition, the issue of multiple control loops is often neglected and consequently self adaptive systems are often designed around a single loop. In this paper we propose a set of design patterns for modeling and designing self adaptive software systems based on MAPE-K. Control loop of IBM architecture blueprint which takes into account the multiple control loops issue. A case study is presented to illustrate the applicability of the proposed design patterns.

  17. Adaptive Data Rates for Flexible Transceivers in Optical Networks

    Brian Thomas Teipen

    2012-05-01

    Full Text Available Efforts towards commercializing higher-speed optical transmission have demonstrated the need for advanced modulation formats, several of which require similar transceiver hardware architecture. Adaptive transceivers can be built to have a number of possible operational configurations selected by software. Such software-defined transceiver configurations can create specific modulation formats to support sets of data rates, corresponding tolerances to system impairments, and sets of electronic digital signal processing schemes chosen to best function in a given network environment. In this paper, we discuss possibilities and advantages of reconfigurable, bit-rate flexible transceivers, and their potential applications in future optical networks.

  18. Adaptive Data Filtering of Inertial Sensors with Variable Bandwidth

    Mushfiqul Alam

    2015-02-01

    Full Text Available MEMS (micro-electro-mechanical system-based inertial sensors, i.e., accelerometers and angular rate sensors, are commonly used as a cost-effective solution for the purposes of navigation in a broad spectrum of terrestrial and aerospace applications. These tri-axial inertial sensors form an inertial measurement unit (IMU, which is a core unit of navigation systems. Even if MEMS sensors have an advantage in their size, cost, weight and power consumption, they suffer from bias instability, noisy output and insufficient resolution. Furthermore, the sensor’s behavior can be significantly affected by strong vibration when it operates in harsh environments. All of these constitute conditions require treatment through data processing. As long as the navigation solution is primarily based on using only inertial data, this paper proposes a novel concept in adaptive data pre-processing by using a variable bandwidth filtering. This approach utilizes sinusoidal estimation to continuously adapt the filtering bandwidth of the accelerometer’s data in order to reduce the effects of vibration and sensor noise before attitude estimation is processed. Low frequency vibration generally limits the conditions under which the accelerometers can be used to aid the attitude estimation process, which is primarily based on angular rate data and, thus, decreases its accuracy. In contrast, the proposed pre-processing technique enables using accelerometers as an aiding source by effective data smoothing, even when they are affected by low frequency vibration. Verification of the proposed concept is performed on simulation and real-flight data obtained on an ultra-light aircraft. The results of both types of experiments confirm the suitability of the concept for inertial data pre-processing.

  19. Adaptive data filtering of inertial sensors with variable bandwidth.

    Alam, Mushfiqul; Rohac, Jan

    2015-01-01

    MEMS (micro-electro-mechanical system)-based inertial sensors, i.e., accelerometers and angular rate sensors, are commonly used as a cost-effective solution for the purposes of navigation in a broad spectrum of terrestrial and aerospace applications. These tri-axial inertial sensors form an inertial measurement unit (IMU), which is a core unit of navigation systems. Even if MEMS sensors have an advantage in their size, cost, weight and power consumption, they suffer from bias instability, noisy output and insufficient resolution. Furthermore, the sensor's behavior can be significantly affected by strong vibration when it operates in harsh environments. All of these constitute conditions require treatment through data processing. As long as the navigation solution is primarily based on using only inertial data, this paper proposes a novel concept in adaptive data pre-processing by using a variable bandwidth filtering. This approach utilizes sinusoidal estimation to continuously adapt the filtering bandwidth of the accelerometer's data in order to reduce the effects of vibration and sensor noise before attitude estimation is processed. Low frequency vibration generally limits the conditions under which the accelerometers can be used to aid the attitude estimation process, which is primarily based on angular rate data and, thus, decreases its accuracy. In contrast, the proposed pre-processing technique enables using accelerometers as an aiding source by effective data smoothing, even when they are affected by low frequency vibration. Verification of the proposed concept is performed on simulation and real-flight data obtained on an ultra-light aircraft. The results of both types of experiments confirm the suitability of the concept for inertial data pre-processing. PMID:25648711

  20. An adaptive association test for microbiome data

    Wu, Chong; Chen, Jun; Kim, Junghi; Pan, Wei

    2016-01-01

    There is increasing interest in investigating how the compositions of microbial communities are associated with human health and disease. Although existing methods have identified many associations, a proper choice of a phylogenetic distance is critical for the power of these methods. To assess an overall association between the composition of a microbial community and an outcome of interest, we present a novel multivariate testing method called aMiSPU, that is joint and highly adaptive over ...

  1. Operational Network Intrusion Detection

    Dreger, Holger

    2008-01-01

    The goal of this thesis is to examine dependencies and tradeoffs between the resource usage (CPU and memory) and the analysis capabilities of Network Intrusion Detection Systems (NIDS). We base our work on the experience of running NIDS in large network environments (among them the Münchener Wissenschaftsnetz (MWN)). These show that resource management is vital for running NIDS in high volume networks. To reduce the resource consumption of NIDS is often only possible by reducing the NIDS' ana...

  2. Perimeter intrusion sensors

    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

  3. Surface Operations Data Analysis and Adaptation Tool Project

    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...

  4. The Burakovskii layered complex (Southern Karelia) as a result of juxtaposition of two intrusions: petrological and isotopic-geochemical data

    The age of base and ultrabase rocks of Aganozerski body (AB) and Shalozersk-Burakovski intrusive body (SBB), forming the Burakovski layered pluton in the Southern Karelia, was determined using the methods of Sm-Nd-, Rb-Sr- and Pb-Pb - dating. Isotopic age of AB made up 2374±29 mln. years, whereas SBB age proved 2433±28 mln. years. Results of the isotopic studies suggest that AB, being 50 mln. years younger than SBB, is a younger independent intrusion

  5. SDR implementation of the receiver of adaptive communication system

    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.

  6. Fatigue, workload and adaptive driver systems

    Hancock, P.A.; Verwey, W.B.

    1997-01-01

    This paper is directed to the further understanding of the problems of fatigue and workload and their role in diminishing driving capability. We present a specific strategy designed to defend against the adverse effects of fatigue and workload extremes through the use of adaptive driver systems. To

  7. The Elements Of Adaptive Neural Expert Systems

    Healy, Michael J.

    1989-03-01

    The generalization properties of a class of neural architectures can be modelled mathematically. The model is a parallel predicate calculus based on pattern recognition and self-organization of long-term memory in a neural network. It may provide the basis for adaptive expert systems capable of inductive learning and rapid processing in a highly complex and changing environment.

  8. Adaptive control system for gas producing wells

    Optimal adaptive automatic control system for gas producing wells cluster is proposed intended for solving the problem of stabilization of the output gas pressure in the cluster at conditions of changing gas flow rate and changing parameters of the wells themselves, providing the maximum high resource of hardware elements of automation

  9. Adaptive P300 based control system

    Jin J; Allison B.Z.; Sellers E.W.; Brunner & C.; Horki P.; Wang X; Neuper C.

    2011-01-01

    An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e., 12 columns and 7 rows). The 9- and 14-flash A & B paradigms present all items of the 12 × 7 matrix three times using either nine or 14 flashes (instead of 19), decreasi...

  10. An Instance-Learning-Based Intrusion-Detection System for Wireless Sensor Networks

    Shuai Fu; Xiaoyan Wang; Jie Li

    2015-01-01

    This paper proposes an instance⁃learning⁃based intrusion⁃detection system (IL⁃IDS) for wireless sensor networks (WSNs). The goal of the proposed system is to detect routing attacks on a WSN. Taking an existing instance⁃learning algorithm for wired networks as our basis, we propose IL⁃IDS for handling routing security problems in a WSN. Attacks on a routing protocol for a WSN include black hole attack and sinkhole attack. The basic idea of our system is to differentiate the changes between secure instances and attack instances. Considering the limited resources of sensor nodes, the existing algorithm cannot be used directly in a WSN. Our system mainly comprises four parts: feature vector selection, threshold selection, instance data processing, and instance determina⁃tion. We create a feature vector form composed of the attributes that changes obviously when an attack occurs within the network. For the data processing in resource⁃constrained sensor nodes, we propose a data⁃reduction scheme based on the clustering algo⁃rithm. For instance determination, we provide a threshold⁃selection scheme and describe the concrete⁃instance⁃determination mechanism of the system. Finally, we simulate and evaluate the proposed IL⁃IDS for different types of attacks.

  11. Aging of the Immune System: How Much Can the Adaptive Immune System Adapt?

    Weng, Nan-ping

    2006-01-01

    The competency of the adaptive immune function decreases with age, primarily because of the decline in production of naïve lymphocytes in the bone marrow and thymus as well as the expansion of incompetent memory lymphocytes. Here I discuss the recent progress on age-associated changes in lymphocytes and their effect on the adaptive immune system.

  12. Adaptive scheduling for shared window joins over data streams

    JIN Cheqing; ZHOU Aoying; Jeffrey Xu Yu; Joshua Zhexue Huang; CAO Feng

    2007-01-01

    Recently a few Continuous Query systems have been developed to cope with applications involving continuous data streams.At the same time,numerous algorithms are proposed for better performance.A recent work on this subject was to define scheduling strategies on shared window joins over data streams from multiple query expressions.In these strategies,a tuple with the highest priority is selected to process from multiple candidates.However,the performance of these static strategies is deeply influenced when data are bursting,because the priority is determined only by static information,such as the query windows,arriving order,etc.In this paper,we propose a novel adaptive strategy where the priority of a tuple is integrated with realtime information.A thorough experimental evaluation has demonstrated that this new strategy can outperform the existing strategies.

  13. Feature Selection Using Particle Swarm Optimization in Intrusion Detection

    Iftikhar Ahmad

    2015-01-01

    The prevention of intrusion in networks is decisive and an intrusion detection system is extremely desirable with potent intrusion detection mechanism. Excessive work is done on intrusion detection systems but still these are not powerful due to high number of false alarms. One of the leading causes of false alarms is due to the usage of a raw dataset that contains redundancy. To resolve this issue, feature selection is necessary which can improve intrusion detection performance. Latterly, pr...

  14. Adaptable Transponder for Multiple Telemetry Systems

    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.

  15. Intrusive images and intrusive thoughts as different phenomena: Two experimental studies

    Hagenaars, M.A.; Brewin, C.R.; Minnen, A. van; Holmes, E.A.; Hoogduin, C.A.L.

    2010-01-01

    According to the dual representation theory of PTSD, intrusive trauma images and intrusive verbal thoughts are produced by separate memory systems. In a previous article it was shown that after watching an aversive film, participants in non-movement conditions reported more intrusive images than par

  16. 入侵检测系统发展的研究综述%A Survey on the Development of Intrusion Detection System

    张相锋; 孙玉芳

    2003-01-01

    With the fast development of Internet ,more and more computer security affairs appear. Researchers havedeveloped many security mechanisms to improve computer security,including intrusion detection (ID). This paper re-views the history of intrusion detection systems (IDS)and mainstream techniques used in IDS,showing that IDS couldimprove security only provided that it is devised based on the architecture of the target system. From this ,we couldsee the trend of integration of host-oriented,network-oriented and application-oriented IDSs.

  17. Adaptive Distributed Data Structure Management for Parallel CFD Applications

    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.

  18. 轻量级无线网络入侵检测系统%Lightweight Wireless Lan Intrusion Detection System

    殷立峰; 吴剑; 马宾

    2012-01-01

    Aiming at wireless network attacks such as DoS attacks,rouge STA, rouge AP,WarDriving attacks and bruteforce attacks, a Lightweight Intrusion Detection System for WLAN is implemented by combining the misuse detection and anomaly detection. In this system,the user can define attack rule set, authorization AP/STA list, illegal AP/STA list, and the sensitivity and the threshold value of detection can adjust according to the circumstance and user requirement. The test shows that this system has a better detecting effect than other WLAN intrusion detection in market.%针对当前流行的无线拒绝服务DoS、伪装STA、伪装AP、WarDriving、暴力破解等无线网络攻击,采用误用检测和异常检测结合的方式,设计并实现了一个针对无线局域网的轻量级无线网络入侵检测系统.系统采用用户自定义攻击规则库、自定义授权AP/STA名单、自定义非法AP/STA名单等方式,能针对无线网络具体环境和用户的不同需要,合理调整入侵检测灵敏度和攻击检测阈值.仿真试验表明,与市场上同类系统相比较,本系统能有效提高无线网络入侵检测效率,大大降低误报率和漏报率.

  19. ADAPTING LINUX AS MOBILE OPERATING SYSTEM

    Kaushik Velusamy

    2013-01-01

    Full Text Available In this fast growing world, people are increasingly mobile; everything is fast, connected and highly secured. All these have put up the requirements on mobile devices and leads to several features being added in the mobile operating systems and its architecture. The development of the next generation software platform based on Linux for mobile phones provides enhanced user experience, power management, cloud support and openness in the design. In spite of many studies on Linux, the investigations on the challenges and benefits of reusing and adapting the Linux kernel to mobile platforms is very less. In this study, a study on architecture of the Linux, its adaptations for a mobile operating system, requirements and analysis for Linux mobile phones, comparison with android and solution technologies to satisfy the requirements for a Linux mobile operating system are analysed and discussed."

  20. Two Perspectives on Information System Adaptation

    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...... 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....... We address this limitation by showing how sensemaking theory can be combined with institutional theory to understand IS adaptation in organizations. Based on a literature review, we present the main assumptions behind institutional and sensemaking theory when used as analytical lenses for...