Rapid deployment intrusion detection system

International Nuclear Information System (INIS)

Graham, R.H.

1997-01-01

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

A Frequency-Based Approach to Intrusion Detection

Directory of Open Access Journals (Sweden)

Mian Zhou

2004-06-01

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

Research on IPv6 intrusion detection system Snort-based

Science.gov (United States)

Shen, Zihao; Wang, Hui

2010-07-01

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

A Fusion of Multiagent Functionalities for Effective Intrusion Detection System

OpenAIRE

Dhanalakshmi Krishnan Sadhasivan; Kannapiran Balasubramanian

2017-01-01

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

Smart sensor systems for outdoor intrusion detection

International Nuclear Information System (INIS)

Lynn, J.K.

1988-01-01

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

Network Intrusion Forensic Analysis Using Intrusion Detection System

OpenAIRE

Manish Kumar; Dr. M. Hanumanthappa; Dr. T.V. Suresh Kumar

2011-01-01

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 investi...

Neural Network Based Intrusion Detection System for Critical Infrastructures

Energy Technology Data Exchange (ETDEWEB)

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.

When Intrusion Detection Meets Blockchain Technology: A Review

DEFF Research Database (Denmark)

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

2018-01-01

developed, which allow IDS nodes to exchange data with each other. However, data and trust management still remain two challenges for current detection architectures, which may degrade the effectiveness of such detection systems. In recent years, blockchain technology has shown its adaptability in many...... fields such as supply chain management, international payment, interbanking and so on. As blockchain can protect the integrity of data storage and ensure process transparency, it has a potential to be applied to intrusion detection domain. Motivated by this, this work provides a review regarding...... the intersection of IDSs and blockchains. In particular, we introduce the background of intrusion detection and blockchain, discuss the applicability of blockchain to intrusion detection, and identify open challenges in this direction....

Security Enrichment in Intrusion Detection System Using Classifier Ensemble

Directory of Open Access Journals (Sweden)

Uma R. Salunkhe

2017-01-01

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

From intrusive to oscillating thoughts.

Science.gov (United States)

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.

Network Intrusion Detection through Stacking Dilated Convolutional Autoencoders

Directory of Open Access Journals (Sweden)

Yang Yu

2017-01-01

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

Data Fusion for Network Intrusion Detection: A Review

Directory of Open Access Journals (Sweden)

Guoquan Li

2018-01-01

Full Text Available Rapid progress of networking technologies leads to an exponential growth in the number of unauthorized or malicious network actions. As a component of defense-in-depth, Network Intrusion Detection System (NIDS has been expected to detect malicious behaviors. Currently, NIDSs are implemented by various classification techniques, but these techniques are not advanced enough to accurately detect complex or synthetic attacks, especially in the situation of facing massive high-dimensional data. Besides, the inherent defects of NIDSs, namely, high false alarm rate and low detection rate, have not been effectively solved. In order to solve these problems, data fusion (DF has been applied into network intrusion detection and has achieved good results. However, the literature still lacks thorough analysis and evaluation on data fusion techniques in the field of intrusion detection. Therefore, it is necessary to conduct a comprehensive review on them. In this article, we focus on DF techniques for network intrusion detection and propose a specific definition to describe it. We review the recent advances of DF techniques and propose a series of criteria to compare their performance. Finally, based on the results of the literature review, a number of open issues and future research directions are proposed at the end of this work.

An intrusion detection system based on fiber hydrophone

Science.gov (United States)

Liu, Junrong; Qiu, Xiufen; Shen, Heping

2017-10-01

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

Interior intrusion alarm systems

International Nuclear Information System (INIS)

Prell, J.A.

1978-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-02-28

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

Anomaly-based intrusion detection for SCADA systems

International Nuclear Information System (INIS)

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

2006-01-01

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

Data mining approach to web application intrusions detection

Science.gov (United States)

Kalicki, Arkadiusz

2011-10-01

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

A Real-Time Intrusion Detection System using Data Mining Technique

Directory of Open Access Journals (Sweden)

Fang-Yie Leu

2008-04-01

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

Hybrid Intrusion Forecasting Framework for Early Warning System

Science.gov (United States)

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

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

Anomaly-Based Intrusion Detection Systems Utilizing System Call Data

Science.gov (United States)

2012-03-01

52 Table 7. Place Reachability Statistics for Low Level CPN...54 Table 8. Place Reachability Statistics for High Level CPN................................................. 55 Table 9. Password Stealing...the efficiency of traditional anti-virus software tools that are dependent on gigantic , continuously updated databases. Fortunately, Intrusion

Intrusion problematic during water supply systems' operation

Energy Technology Data Exchange (ETDEWEB)

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

2011-07-01

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

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

Science.gov (United States)

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

2013-01-01

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

Non-intrusive Quality Analysis of Monitoring Data

CERN Document Server

Brightwell, M; Suwalska, Anna

2010-01-01

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

A Survey on Anomaly Based Host Intrusion Detection System

Science.gov (United States)

Jose, Shijoe; Malathi, D.; Reddy, Bharath; Jayaseeli, Dorathi

2018-04-01

An intrusion detection system (IDS) is hardware, software or a combination of two, for monitoring network or system activities to detect malicious signs. In computer security, designing a robust intrusion detection system is one of the most fundamental and important problems. The primary function of system is detecting intrusion and gives alerts when user tries to intrusion on timely manner. In these techniques when IDS find out intrusion it will send alert massage to the system administrator. Anomaly detection is an important problem that has been researched within diverse research areas and application domains. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. From the existing anomaly detection techniques, each technique has relative strengths and weaknesses. The current state of the experiment practice in the field of anomaly-based intrusion detection is reviewed and survey recent studies in this. This survey provides a study of existing anomaly detection techniques, and how the techniques used in one area can be applied in another application domain.

Data Mining for Intrusion Detection

Science.gov (United States)

Singhal, Anoop; Jajodia, Sushil

Data Mining Techniques have been successfully applied in many different fields including marketing, manufacturing, fraud detection and network management. Over the past years there is a lot of interest in security technologies such as intrusion detection, cryptography, authentication and firewalls. This chapter discusses the application of Data Mining techniques to computer security. Conclusions are drawn and directions for future research are suggested.

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

Energy Technology Data Exchange (ETDEWEB)

Jared Verba; Michael Milvich

2008-05-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Chen, Yan [Northwesten University

2013-12-05

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

Apriori-based network intrusion detection system

International Nuclear Information System (INIS)

Wang Wenjin; Liu Junrong; Liu Baoxu

2012-01-01

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

Intrusion detection system elements

International Nuclear Information System (INIS)

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

1980-09-01

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

Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

Science.gov (United States)

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

2012-01-01

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

A Fusion of Multiagent Functionalities for Effective Intrusion Detection System

Directory of Open Access Journals (Sweden)

Dhanalakshmi Krishnan Sadhasivan

2017-01-01

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

Nuisance alarm suppression techniques for fibre-optic intrusion detection systems

Science.gov (United States)

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

2012-02-01

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

Resilient Control and Intrusion Detection for SCADA Systems

Science.gov (United States)

2014-05-01

Lowe. The myths and facts behind cyber security risks for industrial control systems . VDE Congress, 2004. [45] I. S. C37.1-1994. Ieee standard...Resilient Control and Intrusion Detection for SCADA Systems Bonnie Xia Zhu Electrical Engineering and Computer Sciences University of California at...3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE Resilient Control and Intrusion Detection for SCADA Systems 5a. CONTRACT

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

Directory of Open Access Journals (Sweden)

Kai Peng

2018-01-01

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

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

Science.gov (United States)

2016-08-01

SUBJECT TERMS supervisory control and data acquisition (SCADA), Modbus, industrial control system, intrusion detection system 16. SECURITY...List of Tables iv Acknowledgments v 1. Background 1 2. iPoid Modbus Packet-Inspection Capability 2 2.1 Software Requirements 2 2.2 Startup ...Mr Curtis Arnold’s support of Industrial Control Systems–Supervisory Control and Data Acquisition research at the US Army Research Laboratory

Numerical Continuation Methods for Intrusive Uncertainty Quantification Studies

Energy Technology Data Exchange (ETDEWEB)

Safta, Cosmin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Najm, Habib N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Phipps, Eric Todd [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2014-09-01

Rigorous modeling of engineering systems relies on efficient propagation of uncertainty from input parameters to model outputs. In recent years, there has been substantial development of probabilistic polynomial chaos (PC) Uncertainty Quantification (UQ) methods, enabling studies in expensive computational models. One approach, termed ”intrusive”, involving reformulation of the governing equations, has been found to have superior computational performance compared to non-intrusive sampling-based methods in relevant large-scale problems, particularly in the context of emerging architectures. However, the utility of intrusive methods has been severely limited due to detrimental numerical instabilities associated with strong nonlinear physics. Previous methods for stabilizing these constructions tend to add unacceptably high computational costs, particularly in problems with many uncertain parameters. In order to address these challenges, we propose to adapt and improve numerical continuation methods for the robust time integration of intrusive PC system dynamics. We propose adaptive methods, starting with a small uncertainty for which the model has stable behavior and gradually moving to larger uncertainty where the instabilities are rampant, in a manner that provides a suitable solution.

Sensitive Data Protection Based on Intrusion Tolerance in Cloud Computing

OpenAIRE

Jingyu Wang; xuefeng Zheng; Dengliang Luo

2011-01-01

Service integration and supply on-demand coming from cloud computing can significantly improve the utilization of computing resources and reduce power consumption of per service, and effectively avoid the error of computing resources. However, cloud computing is still facing the problem of intrusion tolerance of the cloud computing platform and sensitive data of new enterprise data center. In order to address the problem of intrusion tolerance of cloud computing platform and sensitive data in...

Abstracting audit data for lightweight intrusion detection

KAUST Repository

Wang, Wei

2010-01-01

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

NIST Special Publication on Intrusion Detection Systems

National Research Council Canada - National Science Library

Bace, Rebecca Gurley

2001-01-01

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

Feature Selection of Network Intrusion Data using Genetic Algorithm and Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Iwan Syarif

2016-12-01

Full Text Available This paper describes the advantages of using Evolutionary Algorithms (EA for feature selection on network intrusion dataset. Most current Network Intrusion Detection Systems (NIDS are unable to detect intrusions in real time because of high dimensional data produced during daily operation. Extracting knowledge from huge data such as intrusion data requires new approach. The more complex the datasets, the higher computation time and the harder they are to be interpreted and analyzed. This paper investigates the performance of feature selection algoritms in network intrusiona data. We used Genetic Algorithms (GA and Particle Swarm Optimizations (PSO as feature selection algorithms. When applied to network intrusion datasets, both GA and PSO have significantly reduces the number of features. Our experiments show that GA successfully reduces the number of attributes from 41 to 15 while PSO reduces the number of attributes from 41 to 9. Using k Nearest Neighbour (k-NN as a classifier,the GA-reduced dataset which consists of 37% of original attributes, has accuracy improvement from 99.28% to 99.70% and its execution time is also 4.8 faster than the execution time of original dataset. Using the same classifier, PSO-reduced dataset which consists of 22% of original attributes, has the fastest execution time (7.2 times faster than the execution time of original datasets. However, its accuracy is slightly reduced 0.02% from 99.28% to 99.26%. Overall, both GA and PSO are good solution as feature selection techniques because theyhave shown very good performance in reducing the number of features significantly while still maintaining and sometimes improving the classification accuracy as well as reducing the computation time.

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

Directory of Open Access Journals (Sweden)

Nabeela Ashraf

2018-01-01

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

An ontology-based intrusion patterns classification system | Shonubi ...

African Journals Online (AJOL)

Studies have shown that computer intrusions have been on the increase in recent times. Many techniques and patterns are being used by intruders to gain access to data on host computer networks. In this work, intrusion patterns were identified and classified and inherent knowledge were represented using an ontology of ...

Intrusion Detection amp Prevention Systems - Sourcefire Snort

Directory of Open Access Journals (Sweden)

Rajesh Vuppala

2015-08-01

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

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

Directory of Open Access Journals (Sweden)

Etienne Waleckx

2015-05-01

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

In-situ trainable intrusion detection system

Energy Technology Data Exchange (ETDEWEB)

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

2016-11-15

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

Intrusive trauma memory: A review and functional analysis

NARCIS (Netherlands)

Krans, J.; Näring, G.W.B.; Becker, E.S.; Holmes, E.A.

2009-01-01

Our contribution to this special issue focuses on the phenomenon of intrusive trauma memory. While intrusive trauma memories can undoubtedly cause impairment, we argue that they may exist for a potentially adaptive reason. Theory and experimental research on intrusion development are reviewed and

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

Directory of Open Access Journals (Sweden)

VANCEA, F.

2014-11-01

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

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

Science.gov (United States)

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

Computational neural network regression model for Host based Intrusion Detection System

Directory of Open Access Journals (Sweden)

Sunil Kumar Gautam

2016-09-01

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

Abstracting massive data for lightweight intrusion detection in computer networks

KAUST Repository

Wang, Wei

2016-10-15

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

Semantic intrusion detection with multisensor data fusion using ...

Indian Academy of Sciences (India)

spatiotemporal relations to form complex events which model the intrusion patterns. ... Wireless sensor networks; complex event processing; event stream; ...... of the 2006 ACM SIGMOD International Conference on Management of Data, 407– ...

AdaBoost-based algorithm for network intrusion detection.

Science.gov (United States)

Hu, Weiming; Hu, Wei; Maybank, Steve

2008-04-01

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

Adaptable data management for systems biology investigations

Directory of Open Access Journals (Sweden)

Burdick David

2009-03-01

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

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

KAUST Repository

Zhang, Xiangliang

2010-01-01

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

Effects of igneous intrusions on the petroleum system: a review

NARCIS (Netherlands)

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

2017-01-01

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

A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification

Science.gov (United States)

Shyu, Mei-Ling; Sainani, Varsha

The increasing number of network security related incidents have made it necessary for the organizations to actively protect their sensitive data with network intrusion detection systems (IDSs). IDSs are expected to analyze a large volume of data while not placing a significantly added load on the monitoring systems and networks. This requires good data mining strategies which take less time and give accurate results. In this study, a novel data mining assisted multiagent-based intrusion detection system (DMAS-IDS) is proposed, particularly with the support of multiclass supervised classification. These agents can detect and take predefined actions against malicious activities, and data mining techniques can help detect them. Our proposed DMAS-IDS shows superior performance compared to central sniffing IDS techniques, and saves network resources compared to other distributed IDS with mobile agents that activate too many sniffers causing bottlenecks in the network. This is one of the major motivations to use a distributed model based on multiagent platform along with a supervised classification technique.

Revisiting Anomaly-based Network Intrusion Detection Systems

NARCIS (Netherlands)

Bolzoni, D.

2009-01-01

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

Hybrid feature selection for supporting lightweight intrusion detection systems

Science.gov (United States)

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

2017-08-01

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

A subtractive approach to interior intrusion detection system design

International Nuclear Information System (INIS)

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

1986-01-01

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

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

Science.gov (United States)

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

2009-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

Alerts Analysis and Visualization in Network-based Intrusion Detection Systems

Energy Technology Data Exchange (ETDEWEB)

Yang, Dr. Li [University of Tennessee

2010-08-01

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

Smart container UWB sensor system for situational awareness of intrusion alarms

Science.gov (United States)

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

2013-06-11

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

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

Institute of Scientific and Technical Information of China (English)

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

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

Directory of Open Access Journals (Sweden)

Sungwon Lee

2009-05-01

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

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

Science.gov (United States)

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

2017-01-01

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

The design about the intrusion defense system for IHEP

International Nuclear Information System (INIS)

Liu Baoxu; Xu Rongsheng; Yu Chuansong; Wu Chunzhen

2003-01-01

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

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

Science.gov (United States)

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.

On Emulation-Based Network Intrusion Detection Systems

NARCIS (Netherlands)

Abbasi, Ali; Wetzel, Jos; Bokslag, Wouter; Zambon, Emmanuele; Etalle, Sandro

2014-01-01

Emulation-based network intrusion detection systems have been devised to detect the presence of shellcode in network traffic by trying to execute (portions of) the network packet payloads in an in- strumented environment and checking the execution traces for signs of shellcode activity.

On emulation-based network intrusion detection systems

NARCIS (Netherlands)

Abbasi, A.; Wetzels, J.; Bokslag, W.; Zambon, E.; Etalle, S.; Stavrou, A.; Bos, H.; Portokalidis, G.

2014-01-01

Emulation-based network intrusion detection systems have been devised to detect the presence of shellcode in network traffic by trying to execute (portions of) the network packet payloads in an instrumented environment and checking the execution traces for signs of shellcode activity.

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

Science.gov (United States)

Sumriddetchkajorn, Sarun; Intaravanne, Yuttana

2010-04-01

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

Intrusion detection sensors

International Nuclear Information System (INIS)

Williams, J.D.

1978-07-01

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

Anomaly-based online intrusion detection system as a sensor for cyber security situational awareness system

OpenAIRE

Kokkonen, Tero

2016-01-01

Almost all the organisations and even individuals rely on complex structures of data networks and networked computer systems. That complex data ensemble, the cyber domain, provides great opportunities, but at the same time it offers many possible attack vectors that can be abused for cyber vandalism, cyber crime, cyber espionage or cyber terrorism. Those threats produce requirements for cyber security situational awareness and intrusion detection capability. This dissertation conc...

Unique Challenges in WiFi Intrusion Detection

OpenAIRE

Milliken, Jonny

2014-01-01

The Intrusion Detection System (IDS) is a common means of protecting networked systems from attack or malicious misuse. The deployment of an IDS can take many different forms dependent on protocols, usage and cost. This is particularly true of Wireless Intrusion Detection Systems (WIDS) which have many detection challenges associated with data transmission through an open, shared medium, facilitated by fundamental changes at the Physical and MAC layers. WIDS need to be considered in more deta...

Nuclear-power-plant perimeter-intrusion alarm systems

International Nuclear Information System (INIS)

Halsey, D.J.

1982-04-01

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

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

Science.gov (United States)

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

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

Distributed fiber optic moisture intrusion sensing system

Science.gov (United States)

Weiss, Jonathan D.

2003-06-24

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

Nuclear data needs for non-intrusive inspection

International Nuclear Information System (INIS)

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

2000-01-01

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

Nuclear data needs for non-intrusive inspection

International Nuclear Information System (INIS)

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

2001-01-01

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

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

Directory of Open Access Journals (Sweden)

Wenchao Li

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Yuancheng Li

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

A Labeled Data Set For Flow-based Intrusion Detection

NARCIS (Netherlands)

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

2009-01-01

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

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

Science.gov (United States)

Ma, Tao; Wang, Fen; Cheng, Jianjun; Yu, Yang; Chen, Xiaoyun

2016-10-13

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

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

DEFF Research Database (Denmark)

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......, 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 transformed to an electrical resistivity model, after which a geophysical forward response is calculated and compared with the measured geophysical data. This approach was applied for a field site in Santa Cruz County, California, where a time-domain electromagnetic (TDEM) dataset was collected...

Combining Host-based and network-based intrusion detection system

African Journals Online (AJOL)

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

When Intrusion Detection Meets Blockchain Technology: A Review

OpenAIRE

Meng, Weizhi; Tischhauser, Elmar Wolfgang; Wang, Qingju; Wang, Yu; Han, Jinguang

2018-01-01

With the purpose of identifying cyber threats and possible incidents, intrusion detection systems (IDSs) are widely deployed in various computer networks. In order to enhance the detection capability of a single IDS, collaborative intrusion detection networks (or collaborative IDSs) have been developed, which allow IDS nodes to exchange data with each other. However, data and trust management still remain two challenges for current detection architectures, which may degrade the effectiveness ...

Approaches in anomaly-based network intrusion detection systems

NARCIS (Netherlands)

Bolzoni, D.; Etalle, S.; Di Pietro, R.; Mancini, L.V.

2008-01-01

Anomaly-based network intrusion detection systems (NIDSs) can take into consideration packet headers, the payload, or a combination of both. We argue that payload-based approaches are becoming the most effective methods to detect attacks. Nowadays, attacks aim mainly to exploit vulnerabilities at

Approaches in Anomaly-based Network Intrusion Detection Systems

NARCIS (Netherlands)

Bolzoni, D.; Etalle, Sandro

Anomaly-based network intrusion detection systems (NIDSs) can take into consideration packet headers, the payload, or a combination of both. We argue that payload-based approaches are becoming the most effective methods to detect attacks. Nowadays, attacks aim mainly to exploit vulnerabilities at

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

International Nuclear Information System (INIS)

EL-Kafas, A.A.

2011-01-01

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

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

International Nuclear Information System (INIS)

Ramadan, A.B.; Hefnawi, M.; Hefnaw, M.

2006-01-01

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

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

DEFF Research Database (Denmark)

Meng, Weizhi; Li, Wenjuan; Su, Chunhua

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Nicoleta STANCIU

2013-01-01

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

Conjunctive Management of Multi-Aquifer System for Saltwater Intrusion Mitigation

Science.gov (United States)

Tsai, F. T. C.; Pham, H. V.

2015-12-01

Due to excessive groundwater withdrawals, many water wells in Baton Rouge, Louisiana experience undesirable chloride concentration because of saltwater intrusion. The study goal is to develop a conjunctive management framework that takes advantage of the Baton Rouge multi-aquifer system to mitigate saltwater intrusion. The conjunctive management framework utilizes several hydraulic control techniques to mitigate saltwater encroachment. These hydraulic control approaches include pumping well relocation, freshwater injection, saltwater scavenging, and their combinations. Specific objectives of the study are: (1) constructing scientific geologic architectures of the "800-foot" sand, the "1,000-foot" sand, the "1,200-foot" sand, the "1,500-foot" sand, the "1,700-foot" sand, and the "2,000-foot" sand, (2) developing scientific saltwater intrusion models for these sands. (3) using connector wells to draw native groundwater from one sand and inject to another sand to create hydraulic barriers to halt saltwater intrusion, (4) using scavenger wells or well couples to impede saltwater intrusion progress and reduce chloride concentration in pumping wells, and (5) reducing cones of depression by relocating and dispersing pumping wells to different sands. The study utilizes optimization techniques and newest LSU high performance computing (HPC) facilities to derive solutions. The conjunctive management framework serves as a scientific tool to assist policy makers to solve the urgent saltwater encroachment issue in the Baton Rouge area. The research results will help water companies as well as industries in East Baton Rouge Parish and neighboring parishes by reducing their saltwater intrusion threats, which in turn would sustain Capital Area economic development.

Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

Science.gov (United States)

Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

2014-01-01

Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

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

Directory of Open Access Journals (Sweden)

Waqas Haider

2016-07-01

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

Implementing an Intrusion Detection System in the Mysea Architecture

National Research Council Canada - National Science Library

Tenhunen, Thomas

2008-01-01

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

Perimeter intrusion detection and assessment system

International Nuclear Information System (INIS)

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

1977-11-01

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

Predicting Seawater Intrusion in Coastal Groundwater Boreholes Using Self-Potential Data

Science.gov (United States)

Graham, M.; MacAllister, D. J.; Jackson, M.; Vinogradov, J.; Butler, A. P.

2017-12-01

Many coastal groundwater abstraction wells are under threat from seawater intrusion: this is exacerbated in summer by low water tables and increased abstraction. Existing hydrochemistry or geophysical techniques often fail to predict the timing of intrusion events. We investigate whether the presence and transport of seawater can influence self-potentials (SPs) measured within groundwater boreholes, with the aim of using SP monitoring to provide early warning of saline intrusion. SP data collection: SP data were collected from a coastal groundwater borehole and an inland borehole (> 60 km from the coast) in the Seaford Chalk of southern England. The SP gradient in the inland borehole was approximately 0.05 mV/m, while that in the coastal borehole varied from 0.16-0.26 mV/m throughout the monitoring period. Spectral analysis showed that semi-diurnal fluctuations in the SP gradient were several orders of magnitude higher at the coast than inland, indicating a strong influence from oceanic tides. A characteristic decrease in the gradient, or precursor, was observed in the coastal borehole several days prior to seawater intrusion. Modelling results: Hydrodynamic transport and geoelectric modelling suggest that observed pressure changes (associated with the streaming potential) are insufficient to explain either the magnitude of the coastal SP gradient or the semi-diurnal SP fluctuations. By contrast, a model of the exclusion-diffusion potential closely matches these observations and produces a precursor similar to that observed in the field. Sensitivity analysis suggests that both a sharp saline front and spatial variations in the exclusion efficiency arising from aquifer heterogeneities are necessary to explain the SP gradient observed in the coastal borehole. The presence of the precursor in the model depends also on the presence and depth of fractures near the base of the borehole. Conclusions: Our results indicate that SP monitoring, combined with hydrodynamic

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

DEFF Research Database (Denmark)

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

context. The validity of a conceptual model is determined by different factors, where both data quantity and quality is of crucial importance. Often, when dealing with saltwater intrusion, data is limited. Therefore, using different sources (and types) of data can be beneficial and increase......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...

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

Directory of Open Access Journals (Sweden)

S. Devaraju

2014-04-01

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

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

Science.gov (United States)

Conrads, Paul; Edwin Roehl, Jr.

2017-01-01

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

A Partially Distributed Intrusion Detection System for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Eung Jun Cho

2013-11-01

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

Securing Cloud Computing from Different Attacks Using Intrusion Detection Systems

Directory of Open Access Journals (Sweden)

Omar Achbarou

2017-03-01

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

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

Data.gov (United States)

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

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

National Research Council Canada - National Science Library

McKay, Thomas D

2006-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-10-15

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

Medication Adherence using Non-intrusive Wearable Sensors

Directory of Open Access Journals (Sweden)

T. H. Lim

2017-12-01

Full Text Available Activity recognition approaches have been applied in home ambient systems to monitor the status and well- being of occupant especially for home care systems. With the advancement of embedded wireless sensing devices, various applications have been proposed to monitor user´s activities and maintain a healthy lifestyle. In this paper, we propose and evaluate a Smart Medication Alert and Treatment Electronic Systems (SmartMATES using a non-intrusive wearable activity recognition sensing system to monitor and alert an user for missing medication prescription. Two sensors are used to collect data from the accelerometer and radio transceiver. Based on the data collected, SmartMATES processes the data and generate a model for the various actions including taking medication. We have evaluated the SmartMATES on 9 participants. The results show that the SmartMATES can identify and prevent missing dosage in a less intrusive way than existing mobile application and traditional approaches.

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

Data.gov (United States)

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

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

Data.gov (United States)

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

Zero Trust Intrusion Containment for Telemedicine

National Research Council Canada - National Science Library

Sood, Arun

2002-01-01

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

Alerts Visualization and Clustering in Network-based Intrusion Detection

Energy Technology Data Exchange (ETDEWEB)

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

2010-04-01

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

Managing saltwater intrusion in coastal arid regions and its societal implications for agriculture

Directory of Open Access Journals (Sweden)

J. Grundmann

2016-05-01

Full Text Available Coastal aquifers in arid and semiarid regions are particularly at risk due to intrusion of salty marine water. Since groundwater is predominantly used in irrigated agriculture, its excessive pumping – above the natural rate of replenishment – strengthen the intrusion process. Using this increasingly saline water for irrigation, leads to a destruction of valuable agricultural resources and the economic basis of farmers and their communities. The limitation of resources (water and soil in these regions requires a societal adaptation and change in behaviour as well as the development of appropriate management strategies for a transition towards stable and sustainable future hydrosystem states. Besides a description of the system dynamics and the spatial consequences of adaptation on the resources availability, the contribution combines results of an empirical survey with stakeholders and physically based modelling of the groundwater-agriculture hydrosystem interactions. This includes an analysis of stakeholders' (farmers and decision makers behaviour and opinions regarding several management interventions aiming on water demand and water resources management as well as the thinking of decision makers how farmers will behave. In this context, the technical counter measures to manage the saltwater intrusion by simulating different groundwater pumping strategies and scenarios are evaluated from the economic and social point of view and if the spatial variability of the aquifer's hydrogeology is taken into consideration. The study is exemplarily investigated for the south Batinah region in the Sultanate of Oman, which is affected by saltwater intrusion into a coastal aquifer system due to excessive groundwater withdrawal for irrigated agriculture.

Detection of network attacks based on adaptive resonance theory

Science.gov (United States)

Bukhanov, D. G.; Polyakov, V. M.

2018-05-01

The paper considers an approach to intrusion detection systems using a neural network of adaptive resonant theory. It suggests the structure of an intrusion detection system consisting of two types of program modules. The first module manages connections of user applications by preventing the undesirable ones. The second analyzes the incoming network traffic parameters to check potential network attacks. After attack detection, it notifies the required stations using a secure transmission channel. The paper describes the experiment on the detection and recognition of network attacks using the test selection. It also compares the obtained results with similar experiments carried out by other authors. It gives findings and conclusions on the sufficiency of the proposed approach. The obtained information confirms the sufficiency of applying the neural networks of adaptive resonant theory to analyze network traffic within the intrusion detection system.

Intrusion Detection System In IoT

OpenAIRE

Nygaard, Frederik

2017-01-01

Intrusion detection detects misbehaving nodes in a network. In Internet of Things(IoT), IPv6 Routing for Low-Power and Lossy Networks (RPL) is the standard routing protocol. In IoT, devices commonly have low energy, storage and memory, which is why the implemented intrusion algorithm in this thesis will try to minimize the usage of these resources. IDS for RPL-networks have been implemented before, but the use of resources or the number of packets sent was too high to be successful when findi...

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

OpenAIRE

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

2013-01-01

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

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

Science.gov (United States)

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

2017-08-01

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

Vulnerability and Risk of Agro-ecosystems Facing Increased Salinity Intrusion in the Mekong Delta, Viet Nam

Science.gov (United States)

Renaud, F.; Sebesvari, Z.; Nguyen, M. T.; Hagenlocher, M.

2016-12-01

The Vietnamese portion of the Mekong Delta increasingly suffers from salinity intrusion in its freshwater system, as exemplified by the historically high salinity levels recorded during the 2016 dry season. Although this exceptional situation was linked to the El Niño phenomena, many factors contribute to an increasing salinization of coastal areas. Salinity intrusion is a natural process in this tidal area but its extent is increasing and projected to worsen due to increased demand for water, diversion/storage of water flows in the Mekong river and its tributaries, land subsidence linked to groundwater over-abstraction, changes in land use and water management in coastal areas, and sea level rise. The Mekong Delta remains predominantly an agricultural landscape which contributes the majority of the rice, aquaculture, and fruit production of the country. These systems will need to be adapted to increased salinity levels. We will present results from two research projects, DeltAdapt and DELTAS, which were designed to allow understanding of, respectively (1) the main drivers of change of agro-ecosystems in coastal areas of the delta and (2) the relative vulnerabilities and risks deltaic social-ecological systems face with respect to various environmental hazards. We used the Global Delta Vulnerability Index developed within the DELTAS project to characterize the vulnerabilities and risks faced by coastal provinces of the delta with respect to salinity intrusion. The analysis allows us to understand which social, economic, and ecological variables index explain the relative vulnerability of the provinces. In addition, drivers of change (e.g. policy, economic, social, environmental) of coastal agro-ecosystems were systematically analyzed through 80 interviews and 7 focus group discussions in the provinces of Kien Giang and Soc Trang within the DeltAdapt project. This was combined with the analysis of Vietnamese policies to determine which are the important drivers of

Intrusion detection techniques for plant-wide network in a nuclear power plant

International Nuclear Information System (INIS)

Rajasekhar, P.; Shrikhande, S.V.; Biswas, B.B.; Patil, R.K.

2012-01-01

Nuclear power plants have a lot of critical data to be sent to the operator workstations. A plant wide integrated communication network, with high throughput, determinism and redundancy, is required between the workstations and the field. Switched Ethernet network is a promising prospect for such an integrated communication network. But for such an integrated system, intrusion is a major issue. Hence the network should have an intrusion detection system to make the network data secure and enhance the network availability. Intrusion detection is the process of monitoring the events occurring in a network and analyzing them for signs of possible incidents, which are violations or imminent threats of violation of network security policies, acceptable user policies, or standard security practices. This paper states the various intrusion detection techniques and approaches which are applicable for analysis of a plant wide network. (author)

Ant colony induced decision trees for intrusion detection

CSIR Research Space (South Africa)

Botes, FH

2017-06-01

Full Text Available platform. Intrusion Detection Systems (IDS) analyse network traffic to identify suspicious patterns with the intention to compromise the system. Practitioners train classifiers to classify the data within different categories e.g. malicious or normal...

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

Directory of Open Access Journals (Sweden)

Dulanović Nenad

2008-01-01

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

Ensemble of classifiers based network intrusion detection system performance bound

CSIR Research Space (South Africa)

Mkuzangwe, Nenekazi NP

2017-11-01

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

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

NARCIS (Netherlands)

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

2007-01-01

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

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

Directory of Open Access Journals (Sweden)

Nattawat Khamphakdee

2015-07-01

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

Development of an Assessment Procedure for Seawater Intrusion Mitigation

Science.gov (United States)

Hsi Ting, F.; Yih Chi, T.

2017-12-01

The Pingtung Plain is one of the areas with extremely plentiful groundwater resources in Taiwan. Due to that the application of the water resource is restricted by significant variation of precipitation between wet and dry seasons, groundwater must be used as a recharge source to implement the insufficient surface water resource during dry seasons. In recent years, the coastal aquaculture rises, and the over withdrawn of groundwater by private well results in fast drop of groundwater level. Then it causes imbalance of groundwater supply and leads to serious seawater intrusion in the coastal areas. The purpose of this study is to develop an integrated numerical model of groundwater resources and seawater intrusion. Soil and Water Assessment Tool (SWAT), MODFLOW and MT3D models were applied to analyze the variation of the groundwater levels and salinity concentration to investigate the correlation of parameters, which are used to the model applications in order to disposal saltwater intrusion. The data of groundwater levels, pumping capacity and hydrogeological data to were collected to build an integrated numerical model. Firstly, we will collect the information of layered aquifer and the data of hydrological parameters to build the groundwater numerical model at Pingtung Plain, and identify the amount of the groundwater which flow into the sea. In order to deal with the future climate change conditions or extreme weather conditions, we will consider the recharge with groundwater model to improve the seawater intrusion problem. The integrated numerical model which describes that seawater intrusion to deep confined aquifers and shallow unsaturated aquifers. Secondly, we will use the above model to investigate the weights influenced by different factors to the amount area of seawater intrusion, and predict the salinity concentration distribution of evaluation at coastal area of Pingtung Plain. Finally, we will simulate groundwater recharge/ injection at the coastal

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

Science.gov (United States)

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

Orthodontic intrusion : Conventional and mini-implant assisted intrusion mechanics

Directory of Open Access Journals (Sweden)

Anup Belludi

2012-01-01

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

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

Science.gov (United States)

2002-04-01

Based Approach to Intrusion Detection System Evaluation for Distributed Real - Time Systems Authors: G. A. Fink, B. L. Chappell, T. G. Turner, and...Distributed, Security. 1 Introduction Processing and cost requirements are driving future naval combat platforms to use distributed, real - time systems of...distributed, real - time systems . As these systems grow more complex, the timing requirements do not diminish; indeed, they may become more constrained

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

Science.gov (United States)

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

2005-11-01

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

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

Science.gov (United States)

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

2017-09-01

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

Hybrid Intrusion Detection System for DDoS Attacks

Directory of Open Access Journals (Sweden)

Özge Cepheli

2016-01-01

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

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

National Research Council Canada - National Science Library

Ye, Nong

2006-01-01

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

Creating a two-layered augmented artificial immune system for application to computer network intrusion detection

Science.gov (United States)

Judge, Matthew G.; Lamont, Gary B.

2009-05-01

Computer network security has become a very serious concern of commercial, industrial, and military organizations due to the increasing number of network threats such as outsider intrusions and insider covert activities. An important security element of course is network intrusion detection which is a difficult real world problem that has been addressed through many different solution attempts. Using an artificial immune system has been shown to be one of the most promising results. By enhancing jREMISA, a multi-objective evolutionary algorithm inspired artificial immune system, with a secondary defense layer; we produce improved accuracy of intrusion classification and a flexibility in responsiveness. This responsiveness can be leveraged to provide a much more powerful and accurate system, through the use of increased processing time and dedicated hardware which has the flexibility of being located out of band.

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

Science.gov (United States)

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

1992-01-01

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

Human intrusion

International Nuclear Information System (INIS)

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

1993-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

Working memory and inhibitory control across the life span: Intrusion errors in the Reading Span Test.

Science.gov (United States)

Robert, Christelle; Borella, Erika; Fagot, Delphine; Lecerf, Thierry; de Ribaupierre, Anik

2009-04-01

The aim of this study was to examine to what extent inhibitory control and working memory capacity are related across the life span. Intrusion errors committed by children and younger and older adults were investigated in two versions of the Reading Span Test. In Experiment 1, a mixed Reading Span Test with items of various list lengths was administered. Older adults and children recalled fewer correct words and produced more intrusions than did young adults. Also, age-related differences were found in the type of intrusions committed. In Experiment 2, an adaptive Reading Span Test was administered, in which the list length of items was adapted to each individual's working memory capacity. Age groups differed neither on correct recall nor on the rate of intrusions, but they differed on the type of intrusions. Altogether, these findings indicate that the availability of attentional resources influences the efficiency of inhibition across the life span.

PyParse: a semiautomated system for scoring spoken recall data.

Science.gov (United States)

Solway, Alec; Geller, Aaron S; Sederberg, Per B; Kahana, Michael J

2010-02-01

Studies of human memory often generate data on the sequence and timing of recalled items, but scoring such data using conventional methods is difficult or impossible. We describe a Python-based semiautomated system that greatly simplifies this task. This software, called PyParse, can easily be used in conjunction with many common experiment authoring systems. Scored data is output in a simple ASCII format and can be accessed with the programming language of choice, allowing for the identification of features such as correct responses, prior-list intrusions, extra-list intrusions, and repetitions.

Volcano monitoring using GPS: Developing data analysis strategies based on the June 2007 Kīlauea Volcano intrusion and eruption

Science.gov (United States)

Larson, Kristine M.; Poland, Michael; Miklius, Asta

2010-01-01

The global positioning system (GPS) is one of the most common techniques, and the current state of the art, used to monitor volcano deformation. In addition to slow (several centimeters per year) displacement rates, GPS can be used to study eruptions and intrusions that result in much larger (tens of centimeters over hours-days) displacements. It is challenging to resolve precise positions using GPS at subdaily time intervals because of error sources such as multipath and atmospheric refraction. In this paper, the impact of errors due to multipath and atmospheric refraction at subdaily periods is examined using data from the GPS network on Kīlauea Volcano, Hawai'i. Methods for filtering position estimates to enhance precision are both simulated and tested on data collected during the June 2007 intrusion and eruption. Comparisons with tiltmeter records show that GPS instruments can precisely recover the timing of the activity.

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

NARCIS (Netherlands)

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

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

Panacea : Automating attack classification for anomaly-based network intrusion detection systems

NARCIS (Netherlands)

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

2009-01-01

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

Panacea : Automating attack classification for anomaly-based network intrusion detection systems

NARCIS (Netherlands)

Bolzoni, D.; Etalle, S.; Hartel, P.H.

2009-01-01

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

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

NARCIS (Netherlands)

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

2009-01-01

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

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

Science.gov (United States)

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

2007-08-01

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

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

Directory of Open Access Journals (Sweden)

A. S. Bozhday

2017-01-01

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

Ensemble Kalman Filter Assimilation of ERT Data for Numerical Modeling of Seawater Intrusion in a Laboratory Experiment

Directory of Open Access Journals (Sweden)

Véronique Bouzaglou

2018-03-01

Full Text Available Seawater intrusion in coastal aquifers is a worldwide problem exacerbated by aquifer overexploitation and climate changes. To limit the deterioration of water quality caused by saline intrusion, research studies are needed to identify and assess the performance of possible countermeasures, e.g., underground barriers. Within this context, numerical models are fundamental to fully understand the process and for evaluating the effectiveness of the proposed solutions to contain the saltwater wedge; on the other hand, they are typically affected by uncertainty on hydrogeological parameters, as well as initial and boundary conditions. Data assimilation methods such as the ensemble Kalman filter (EnKF represent promising tools that can reduce such uncertainties. Here, we present an application of the EnKF to the numerical modeling of a laboratory experiment where seawater intrusion was reproduced in a specifically designed sandbox and continuously monitored with electrical resistivity tomography (ERT. Combining EnKF and the SUTRA model for the simulation of density-dependent flow and transport in porous media, we assimilated the collected ERT data by means of joint and sequential assimilation approaches. In the joint approach, raw ERT data (electrical resistances are assimilated to update both salt concentration and soil parameters, without the need for an electrical inversion. In the sequential approach, we assimilated electrical conductivities computed from a previously performed electrical inversion. Within both approaches, we suggest dual-step update strategies to minimize the effects of spurious correlations in parameter estimation. The results show that, in both cases, ERT data assimilation can reduce the uncertainty not only on the system state in terms of salt concentration, but also on the most relevant soil parameters, i.e., saturated hydraulic conductivity and longitudinal dispersivity. However, the sequential approach is more prone to

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

Directory of Open Access Journals (Sweden)

HUSAIN SHAHNAWAZ

2012-10-01

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

Intrusion detection in wireless ad-hoc networks

CERN Document Server

Chaki, Nabendu

2014-01-01

Presenting cutting-edge research, Intrusion Detection in Wireless Ad-Hoc Networks explores the security aspects of the basic categories of wireless ad-hoc networks and related application areas. Focusing on intrusion detection systems (IDSs), it explains how to establish security solutions for the range of wireless networks, including mobile ad-hoc networks, hybrid wireless networks, and sensor networks.This edited volume reviews and analyzes state-of-the-art IDSs for various wireless ad-hoc networks. It includes case studies on honesty-based intrusion detection systems, cluster oriented-based

Proposed Network Intrusion Detection System ‎Based on Fuzzy c Mean Algorithm in Cloud ‎Computing Environment

Directory of Open Access Journals (Sweden)

Shawq Malik Mehibs

2017-12-01

Full Text Available Nowadays cloud computing had become is an integral part of IT industry, cloud computing provides Working environment allow a user of environmental to share data and resources over the internet. Where cloud computing its virtual grouping of resources offered over the internet, this lead to different matters related to the security and privacy in cloud computing. And therefore, create intrusion detection very important to detect outsider and insider intruders of cloud computing with high detection rate and low false positive alarm in the cloud environment. This work proposed network intrusion detection module using fuzzy c mean algorithm. The kdd99 dataset used for experiments .the proposed system characterized by a high detection rate with low false positive alarm

Large scale applicability of a Fully Adaptive Non-Intrusive Spectral Projection technique: Sensitivity and uncertainty analysis of a transient

International Nuclear Information System (INIS)

Perkó, Zoltán; Lathouwers, Danny; Kloosterman, Jan Leen; Hagen, Tim van der

2014-01-01

Highlights: • Grid and basis adaptive Polynomial Chaos techniques are presented for S and U analysis. • Dimensionality reduction and incremental polynomial order reduce computational costs. • An unprotected loss of flow transient is investigated in a Gas Cooled Fast Reactor. • S and U analysis is performed with MC and adaptive PC methods, for 42 input parameters. • PC accurately estimates means, variances, PDFs, sensitivities and uncertainties. - Abstract: Since the early years of reactor physics the most prominent sensitivity and uncertainty (S and U) analysis methods in the nuclear community have been adjoint based techniques. While these are very effective for pure neutronics problems due to the linearity of the transport equation, they become complicated when coupled non-linear systems are involved. With the continuous increase in computational power such complicated multi-physics problems are becoming progressively tractable, hence affordable and easily applicable S and U analysis tools also have to be developed in parallel. For reactor physics problems for which adjoint methods are prohibitive Polynomial Chaos (PC) techniques offer an attractive alternative to traditional random sampling based approaches. At TU Delft such PC methods have been studied for a number of years and this paper presents a large scale application of our Fully Adaptive Non-Intrusive Spectral Projection (FANISP) algorithm for performing the sensitivity and uncertainty analysis of a Gas Cooled Fast Reactor (GFR) Unprotected Loss Of Flow (ULOF) transient. The transient was simulated using the Cathare 2 code system and a fully detailed model of the GFR2400 reactor design that was investigated in the European FP7 GoFastR project. Several sources of uncertainty were taken into account amounting to an unusually high number of stochastic input parameters (42) and numerous output quantities were investigated. The results show consistently good performance of the applied adaptive PC

AANtID: an alternative approach to network intrusion detection ...

African Journals Online (AJOL)

Journal of Computer Science and Its Application ... Security has become not just a feature of an information system, but the core and a necessity especially the systems that communicate and transmit data over the Internet for they are more ... Keywords: Intrusion, Genetic Algorithm, detection, Security, DARPA dataset ...

New device to measure dynamic intrusion/extrusion cycles of lyophobic heterogeneous systems.

Science.gov (United States)

Guillemot, Ludivine; Galarneau, Anne; Vigier, Gérard; Abensur, Thierry; Charlaix, Élisabeth

2012-10-01

Lyophobic heterogeneous systems (LHS) are made of mesoporous materials immersed in a non-wetting liquid. One application of LHS is the nonlinear damping of high frequency vibrations. The behaviour of LHS is characterized by P - ΔV cycles, where P is the pressure applied to the system, and ΔV its volume change due to the intrusion of the liquid into the pores of the material, or its extrusion out of the pores. Very few dynamic studies of LHS have been performed until now. We describe here a new apparatus that allows us to carry out dynamic intrusion/extrusion cycles with various liquid/porous material systems, controlling the temperature from ambient to 120 °C and the frequency from 0.01 to 20 Hz. We show that for two LHS: water/MTS and Galinstan/CPG, the energy dissipated during one cycle depends very weakly on the cycle frequency, in strong contrast to conventional dampers.

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

International Nuclear Information System (INIS)

Taylor, B.E

2001-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-11-11

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

Intrusion Detection Algorithm for Mitigating Sinkhole Attack on LEACH Protocol in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Ranjeeth Kumar Sundararajan

2015-01-01

Full Text Available In wireless sensor network (WSN, the sensors are deployed and placed uniformly to transmit the sensed data to a centralized station periodically. So, the major threat of the WSN network layer is sinkhole attack and it is still being a challenging issue on the sensor networks, where the malicious node attracts the packets from the other normal sensor nodes and drops the packets. Thus, this paper proposes an Intrusion Detection System (IDS mechanism to detect the intruder in the network which uses Low Energy Adaptive Clustering Hierarchy (LEACH protocol for its routing operation. In the proposed algorithm, the detection metrics, such as number of packets transmitted and received, are used to compute the intrusion ratio (IR by the IDS agent. The computed numeric or nonnumeric value represents the normal or malicious activity. As and when the sinkhole attack is captured, the IDS agent alerts the network to stop the data transmission. Thus, it can be a resilient to the vulnerable attack of sinkhole. Above all, the simulation result is shown for the proposed algorithm which is proven to be efficient compared with the existing work, namely, MS-LEACH, in terms of minimum computational complexity and low energy consumption. Moreover, the algorithm was numerically analyzed using TETCOS NETSIM.

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

Directory of Open Access Journals (Sweden)

Wei Gao

2014-03-01

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

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

Science.gov (United States)

Palano, Mimmo; González, Pablo J.

2013-04-01

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

Specifying the neurobiological basis of human attachment: brain, hormones, and behavior in synchronous and intrusive mothers.

Science.gov (United States)

Atzil, Shir; Hendler, Talma; Feldman, Ruth

2011-12-01

The mother-infant bond provides the foundation for the infant's future mental health and adaptation and depends on the provision of species-typical maternal behaviors that are supported by neuroendocrine and motivation-affective neural systems. Animal research has demonstrated that natural variations in patterns of maternal care chart discrete profiles of maternal brain-behavior relationships that uniquely shape the infant's lifetime capacities for stress regulation and social affiliation. Such patterns of maternal care are mediated by the neuropeptide Oxytocin and by stress- and reward-related neural systems. Human studies have similarly shown that maternal synchrony--the coordination of maternal behavior with infant signals--and intrusiveness--the excessive expression of maternal behavior--describe distinct and stable maternal styles that bear long-term consequences for infant well-being. To integrate brain, hormones, and behavior in the study of maternal-infant bonding, we examined the fMRI responses of synchronous vs intrusive mothers to dynamic, ecologically valid infant videos and their correlations with plasma Oxytocin. In all, 23 mothers were videotaped at home interacting with their infants and plasma OT assayed. Sessions were micro-coded for synchrony and intrusiveness. Mothers were scanned while observing several own and standard infant-related vignettes. Synchronous mothers showed greater activations in the left nucleus accumbens (NAcc) and intrusive mothers exhibited higher activations in the right amygdala. Functional connectivity analysis revealed that among synchronous mothers, left NAcc and right amygdala were functionally correlated with emotion modulation, theory-of-mind, and empathy networks. Among intrusive mothers, left NAcc and right amygdala were functionally correlated with pro-action areas. Sorting points into neighborhood (SPIN) analysis demonstrated that in the synchronous group, left NAcc and right amygdala activations showed clearer

A web-based non-intrusive ambient system to measure and classify activities of daily living.

Science.gov (United States)

Stucki, Reto A; Urwyler, Prabitha; Rampa, Luca; Müri, René; Mosimann, Urs P; Nef, Tobias

2014-07-21

The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. In this study, 10 healthy participants (6 women

A new intrusion prevention model using planning knowledge graph

Science.gov (United States)

Cai, Zengyu; Feng, Yuan; Liu, Shuru; Gan, Yong

2013-03-01

Intelligent plan is a very important research in artificial intelligence, which has applied in network security. This paper proposes a new intrusion prevention model base on planning knowledge graph and discuses the system architecture and characteristics of this model. The Intrusion Prevention based on plan knowledge graph is completed by plan recognition based on planning knowledge graph, and the Intrusion response strategies and actions are completed by the hierarchical task network (HTN) planner in this paper. Intrusion prevention system has the advantages of intelligent planning, which has the advantage of the knowledge-sharing, the response focused, learning autonomy and protective ability.

Geophysical characterization from Itu intrusive suite

International Nuclear Information System (INIS)

Pascholati, M.E.

1989-01-01

The integrated use of geophysical, geological, geochemical, petrographical and remote sensing data resulted in a substantial increase in the knowledge of the Itu Intrusive Suite. The main geophysical method was gamma-ray spectrometry together with fluorimetry and autoradiography. Three methods were used for calculation of laboratory gamma-ray spectrometry data. For U, the regression method was the best one. For K and Th, equations system and absolute calibration presented the best results. Surface gamma-ray spectrometry allowed comparison with laboratory data and permitted important contribution to the study of environmental radiation. (author)

Reading between the fields: practical, effective intrusion detection for industrial control systems

NARCIS (Netherlands)

Yüksel, Ömer; den Hartog, Jeremy; Etalle, Sandro

2016-01-01

Detection of previously unknown attacks and malicious messages is a challenging problem faced by modern network intrusion detection systems. Anomaly-based solutions, despite being able to detect unknown attacks, have not been used often in practice due to their high false positive rate, and because

EU-project AEROJET. Non-intrusive measurements of aircraft engine exhaust emissions

Energy Technology Data Exchange (ETDEWEB)

Schaefer, K.; Heland, J. [Fraunhofer-Inst. fuer Atmosphaerische Umweltforschung (IFU), Garmisch-Partenkirchen (Germany); Burrows, R. [Rolls-Royce Ltd. (United Kingdom). Engine Support Lab.; Bernard, M. [AUXITROL, S.A. (France). Aerospace Equipment Div.; Bishop, G. [British Aerospace (United Kingdom). Sowerby Research Centre; Lindermeir, E. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e. V. (DLR), Bonn (Germany). Inst. fuer Optoelektronik; Lister, D.H. [Defence and Research Agency, Hants (United Kingdom). Propulsion and Development Dept.; Wiesen, P. [Bergische Univ. Wuppertal (Gesamthochshule) (Germany); Hilton, M. [University of Reading (United Kingdom). Dept. of Physics

1997-12-31

The main goal of the AEROJET programme is to demonstrate the equivalence of remote measurement techniques to conventional extractive methods for both gaseous and particulate measurements. The different remote measurement techniques are compared and calibrated. A demonstrator measurement system for exhaust gases, temperature and particulates including data-analysis software is regarded as result of this project. Non-intrusive measurements are the method of choice within the AEROJET project promising to avoid the disadvantages of the gas sampling techniques which are currently used. Different ground based non-intrusive measurement methods are demonstrated during a final evaluation phase. Several non-intrusive techniques are compared with conventional gas sampling and analysis techniques. (R.P.) 3 refs.

EU-project AEROJET. Non-intrusive measurements of aircraft engine exhaust emissions

Energy Technology Data Exchange (ETDEWEB)

Schaefer, K; Heland, J [Fraunhofer-Inst. fuer Atmosphaerische Umweltforschung (IFU), Garmisch-Partenkirchen (Germany); Burrows, R [Rolls-Royce Ltd. (United Kingdom). Engine Support Lab.; Bernard, M [AUXITROL, S.A. (France). Aerospace Equipment Div.; Bishop, G [British Aerospace (United Kingdom). Sowerby Research Centre; Lindermeir, E [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e. V. (DLR), Bonn (Germany). Inst. fuer Optoelektronik; Lister, D H [Defence and Research Agency, Hants (United Kingdom). Propulsion and Development Dept.; Wiesen, P [Bergische Univ. Wuppertal (Gesamthochshule) (Germany); Hilton, M [University of Reading (United Kingdom). Dept. of Physics

1998-12-31

The main goal of the AEROJET programme is to demonstrate the equivalence of remote measurement techniques to conventional extractive methods for both gaseous and particulate measurements. The different remote measurement techniques are compared and calibrated. A demonstrator measurement system for exhaust gases, temperature and particulates including data-analysis software is regarded as result of this project. Non-intrusive measurements are the method of choice within the AEROJET project promising to avoid the disadvantages of the gas sampling techniques which are currently used. Different ground based non-intrusive measurement methods are demonstrated during a final evaluation phase. Several non-intrusive techniques are compared with conventional gas sampling and analysis techniques. (R.P.) 3 refs.

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

International Nuclear Information System (INIS)

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

2011-01-01

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

Biological intrusion barriers for large-volume waste-disposal sites

International Nuclear Information System (INIS)

Hakonson, T.E.; Cline, J.F.; Rickard, W.H.

1982-01-01

intrusion of plants and animals into shallow land burial sites with subsequent mobilization of toxic and radiotoxic materials has occured. Based on recent pathway modeling studies, such intrusions can contribute to the dose received by man. This paper describes past work on developing biological intrusion barrier systems for application to large volume waste site stabilization. State-of-the-art concepts employing rock and chemical barriers are discussed relative to long term serviceability and cost of application. The interaction of bio-intrusion barrier systems with other processes affecting trench cover stability are discussed to ensure that trench cover designs minimize the potential dose to man. 3 figures, 6 tables

Intrusion scenarios in fusion waste disposal sites

International Nuclear Information System (INIS)

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

1998-01-01

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

Intrusion scenarios in fusion waste disposal sites

Energy Technology Data Exchange (ETDEWEB)

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

1998-07-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-02-01

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

Improved Information Retrieval Performance on SQL Database Using Data Adapter

Science.gov (United States)

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

2018-02-01

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

How stratospheric are deep stratospheric intrusions? LUAMI 2008

Directory of Open Access Journals (Sweden)

T. Trickl

2016-07-01

Full Text Available A large-scale comparison of water-vapour vertical-sounding instruments took place over central Europe on 17 October 2008, during a rather homogeneous deep stratospheric intrusion event (LUAMI, Lindenberg Upper-Air Methods Intercomparison. The measurements were carried out at four observational sites: Payerne (Switzerland, Bilthoven (the Netherlands, Lindenberg (north-eastern Germany, and the Zugspitze mountain (Garmisch-Partenkichen, German Alps, and by an airborne water-vapour lidar system creating a transect of humidity profiles between all four stations. A high data quality was verified that strongly underlines the scientific findings. The intrusion layer was very dry with a minimum mixing ratios of 0 to 35 ppm on its lower west side, but did not drop below 120 ppm on the higher-lying east side (Lindenberg. The dryness hardens the findings of a preceding study (“Part 1”, Trickl et al., 2014 that, e.g., 73 % of deep intrusions reaching the German Alps and travelling 6 days or less exhibit minimum mixing ratios of 50 ppm and less. These low values reflect values found in the lowermost stratosphere and indicate very slow mixing with tropospheric air during the downward transport to the lower troposphere. The peak ozone values were around 70 ppb, confirming the idea that intrusion layers depart from the lowermost edge of the stratosphere. The data suggest an increase of ozone from the lower to the higher edge of the intrusion layer. This behaviour is also confirmed by stratospheric aerosol caught in the layer. Both observations are in agreement with the idea that sections of the vertical distributions of these constituents in the source region were transferred to central Europe without major change. LAGRANTO trajectory calculations demonstrated a rather shallow outflow from the stratosphere just above the dynamical tropopause, for the first time confirming the conclusions in “Part 1” from the Zugspitze CO observations. The

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

Science.gov (United States)

Mitra, Sunanda; Pemmaraju, Surya

1992-01-01

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

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

Science.gov (United States)

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

Adaptive security systems -- Combining expert systems with adaptive technologies

International Nuclear Information System (INIS)

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

1997-01-01

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

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

Science.gov (United States)

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

2016-02-01

The aim of this study was to determine the extent and geometrical characteristics of seawater intrusion in the coastal aquifer of the eastern Thermaikos Gulf, Greece. Hydrochemical data and geoelectrical measurements were combined and supplemented to determine the hydrochemical regime of the study site in regard to seawater phenomena. Chemical analysis of groundwater was performed in 126 boreholes and fifteen electrical resistivity tomographies (ERT) were measured, whereas in two sites the ERT measurements were repeated following the wet season. The Cl(-) concentrations recorded reached 2240 mg/L indicating seawater intrusion which was also verified by ionic ratios. The ionic ratios were overlapped and a seawater intrusion map (SWIM) was produced. A significant part of the coastal aquifer (up to 150 km(2)) is influenced by seawater intrusion. The areas with the most intensive salinization are located between Nea Kallikratia-Epanomi and Aggelochori-Peraia. According to the ERTs, in the influenced areas the salinization of the aquifer exceeds 1 km toward the mainland and its depth reaches 200 m. In the area surrounding Thessaloniki airport, the ERTs revealed salinization of the upper aquifer to depths of up to 40 m, whereas the lower aquifer is uninfluenced. This abnormal distribution of seawater intrusion demonstrates the value of geoelectrical methods in the study of seawater intrusion especially in areas with limited available hydrochemical data. Copyright © 2015 Elsevier B.V. All rights reserved.

The state of the art in intrusion prevention and detection

CERN Document Server

Pathan, Al-Sakib Khan

2013-01-01

The State of the Art in Intrusion Prevention and Detection analyzes the latest trends and issues surrounding intrusion detection systems in computer networks, especially in communications networks. Its broad scope of coverage includes wired, wireless, and mobile networks; next-generation converged networks; and intrusion in social networks.Presenting cutting-edge research, the book presents novel schemes for intrusion detection and prevention. It discusses tracing back mobile attackers, secure routing with intrusion prevention, anomaly detection, and AI-based techniques. It also includes infor

CRITICAL INFORMATION INFRASTRUCTURE SECURITY - NETWORK INTRUSION DETECTION SYSTEMS

Directory of Open Access Journals (Sweden)

Cristea DUMITRU

2011-12-01

Full Text Available Critical Information Infrastructure security will always be difficult to ensure, just because of the features that make it irreplaceable tor other critical infrastructures normal operation. It is decentralized, interconnected interdependent, controlled by multiple actors (mainly private and incorporating diverse types of technologies. It is almost axiomatic that the disruption of the Critical Information Infrastructure affects systems located much farther away, and the cyber problems have direct consequences on the real world. Indeed the Internet can be used as a multiplier in order to amplify the effects of an attack on some critical infrastructures. Security challenges increase with the technological progress. One of the last lines of defense which comes to complete the overall security scheme of the Critical Information Infrastructure is represented by the Network Intrusion Detection Systems.

Intrusion problematic during water supply systems’ operation

OpenAIRE

Jesus Mora-Rodriguez, P. Amparo López-Jimenez, Helena M. Ramos

2011-01-01

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 focuse...

Autonomous Rule Creation for Intrusion Detection

Energy Technology Data Exchange (ETDEWEB)

Todd Vollmer; Jim Alves-Foss; Milos Manic

2011-04-01

Many computational intelligence techniques for anomaly based network intrusion detection can be found in literature. Translating a newly discovered intrusion recognition criteria into a distributable rule can be a human intensive effort. This paper explores a multi-modal genetic algorithm solution for autonomous rule creation. This algorithm focuses on the process of creating rules once an intrusion has been identified, rather than the evolution of rules to provide a solution for intrusion detection. The algorithm was demonstrated on anomalous ICMP network packets (input) and Snort rules (output of the algorithm). Output rules were sorted according to a fitness value and any duplicates were removed. The experimental results on ten test cases demonstrated a 100 percent rule alert rate. Out of 33,804 test packets 3 produced false positives. Each test case produced a minimum of three rule variations that could be used as candidates for a production system.

AdiosStMan: Parallelizing Casacore Table Data System using Adaptive IO System

Science.gov (United States)

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.

Experimental study of the interplay between magmatic rift intrusion and flank instability with application to the 2001 Mount Etna eruption

KAUST Repository

Le Corvec, Nicolas

2014-07-01

Mount Etna volcano is subject to transient magmatic intrusions and flank movement. The east flank of the edifice, in particular, is moving eastward and is dissected by the Timpe Fault System. The relationship of this eastward motion with intrusions and tectonic fault motion, however, remains poorly constrained. Here we explore this relationship by using analogue experiments that are designed to simulate magmatic rift intrusion, flank movement, and fault activity before, during, and after a magmatic intrusion episode. Using particle image velocimetry allows for a precise temporal and spatial analysis of the development and activity of fault systems. The results show that the occurrence of rift intrusion episodes has a direct effect on fault activity. In such a situation, fault activity may occur or may be hindered, depending on the interplay of fault displacement and flank acceleration in response to dike intrusion. Our results demonstrate that a complex interplay may exist between an active tectonic fault system and magmatically induced flank instability. Episodes of magmatic intrusion change the intensity pattern of horizontal flank displacements and may hinder or activate associated faults. We further compare our results with the GPS data of the Mount Etna 2001 eruption and intrusion. We find that syneruptive displacement rates at the Timpe Fault System have differed from the preeruptive or posteruptive periods, which shows a good agreement of both the experimental and the GPS data. Therefore, understanding the flank instability and flank stability at Mount Etna requires consideration of both tectonic and magmatic forcing. Key Points Analyzing Mount Etna east flank dynamics during the 2001 eruption Good correlation between analogue models and GPS data Understanding the different behavior of faulting before/during/after an eruption © 2014. American Geophysical Union. All Rights Reserved.

Experimental study of the interplay between magmatic rift intrusion and flank instability with application to the 2001 Mount Etna eruption

KAUST Repository

Le Corvec, Nicolas; Walter, Thomas R.; Ruch, Joel; Bonforte, Alessandro; Puglisi, Giuseppe

2014-01-01

Mount Etna volcano is subject to transient magmatic intrusions and flank movement. The east flank of the edifice, in particular, is moving eastward and is dissected by the Timpe Fault System. The relationship of this eastward motion with intrusions and tectonic fault motion, however, remains poorly constrained. Here we explore this relationship by using analogue experiments that are designed to simulate magmatic rift intrusion, flank movement, and fault activity before, during, and after a magmatic intrusion episode. Using particle image velocimetry allows for a precise temporal and spatial analysis of the development and activity of fault systems. The results show that the occurrence of rift intrusion episodes has a direct effect on fault activity. In such a situation, fault activity may occur or may be hindered, depending on the interplay of fault displacement and flank acceleration in response to dike intrusion. Our results demonstrate that a complex interplay may exist between an active tectonic fault system and magmatically induced flank instability. Episodes of magmatic intrusion change the intensity pattern of horizontal flank displacements and may hinder or activate associated faults. We further compare our results with the GPS data of the Mount Etna 2001 eruption and intrusion. We find that syneruptive displacement rates at the Timpe Fault System have differed from the preeruptive or posteruptive periods, which shows a good agreement of both the experimental and the GPS data. Therefore, understanding the flank instability and flank stability at Mount Etna requires consideration of both tectonic and magmatic forcing. Key Points Analyzing Mount Etna east flank dynamics during the 2001 eruption Good correlation between analogue models and GPS data Understanding the different behavior of faulting before/during/after an eruption © 2014. American Geophysical Union. All Rights Reserved.

Radioactive elements behaviour in multiphase intrusive series and petrological significance of radiogeochemical data

International Nuclear Information System (INIS)

Ponomareva, A.P.; Zlobin, V.A.

1982-01-01

The behaviour of radioactive elements (RE) during formation of multiphase intrusive series of various ages, types and alkalinity nature, placed in different structural formation zones of West Uzbekistan is discussed (on the basis of 230 quantitative determinations). It is established that maximum RE concentrations in the intrusive series considered are U=3-5, Th=11-17 g/t and correspond to granodiorites, adamellites, granites and granosienites. The typical behaviour for U and Th is the growth of their concentrations in the direction from gabbro- to granodiorites (granosienites) and granites, and then decrease to leucocrat granites (alkaline, biotite or bimica ones). The evolution of magmatic systems occurred not along the line of differentiation of melts, but along the line of their ''washing'' with fluid mainly at the level of magma generation and on their way to upper horizons of Earth crust. High concentrations (several times more than a clark) must occur in cases of additional RE introduction

Human intrusion: New ideas?

International Nuclear Information System (INIS)

Cooper, J.R.

2002-01-01

Inadvertent human intrusion has been an issue for the disposal of solid radioactive waste for many years. This paper discusses proposals for an approach for evaluating the radiological significance of human intrusion as put forward by ICRP with contribution from work at IAEA. The approach focuses on the consequences of the intrusion. Protective actions could, however, include steps to reduce the probability of human intrusion as well as the consequences. (author)

Number of Waste Package Hit by Igneous Intrusion

International Nuclear Information System (INIS)

M. Wallace

2004-01-01

The purpose of this scientific analysis report is to document calculations of the number of waste packages that could be damaged in a potential future igneous event through a repository at Yucca Mountain. The analyses include disruption from an intrusive igneous event and from an extrusive volcanic event. This analysis supports the evaluation of the potential consequences of future igneous activity as part of the total system performance assessment for the license application (TSPA-LA) for the Yucca Mountain Project (YMP). Igneous activity is a disruptive event that is included in the TSPA-LA analyses. Two igneous activity scenarios are considered: (1) The igneous intrusion groundwater release scenario (also called the igneous intrusion scenario) considers the in situ damage to waste packages or failure of waste packages that occurs if they are engulfed or otherwise affected by magma as a result of an igneous intrusion. (2) The volcanic eruption scenario depicts the direct release of radioactive waste due to an intrusion that intersects the repository followed by a volcanic eruption at the surface. An igneous intrusion is defined as the ascent of a basaltic dike or dike system (i.e., a set or swarm of multiple dikes comprising a single intrusive event) to repository level, where it intersects drifts. Magma that does reach the surface from igneous activity is an eruption (or extrusive activity) (Jackson 1997 [DIRS 109119], pp. 224, 333). The objective of this analysis is to develop a probabilistic measure of the number of waste packages that could be affected by each of the two scenarios

Network Intrusion Detection System (NIDS in Cloud Environment based on Hidden Naïve Bayes Multiclass Classifier

Directory of Open Access Journals (Sweden)

Hafza A. Mahmood

2018-04-01

Full Text Available Cloud Environment is next generation internet based computing system that supplies customiza-ble services to the end user to work or access to the various cloud applications. In order to provide security and decrease the damage of information system, network and computer system it is im-portant to provide intrusion detection system (IDS. Now Cloud environment are under threads from network intrusions, as one of most prevalent and offensive means Denial of Service (DoS attacks that cause dangerous impact on cloud computing systems. This paper propose Hidden naïve Bayes (HNB Classifier to handle DoS attacks which is a data mining (DM model used to relaxes the conditional independence assumption of Naïve Bayes classifier (NB, proposed sys-tem used HNB Classifier supported with discretization and feature selection where select the best feature enhance the performance of the system and reduce consuming time. To evaluate the per-formance of proposal system, KDD 99 CUP and NSL KDD Datasets has been used. The experi-mental results show that the HNB classifier improves the performance of NIDS in terms of accu-racy and detecting DoS attacks, where the accuracy of detect DoS is 100% in three test KDD cup 99 dataset by used only 12 feature that selected by use gain ratio while in NSL KDD Dataset the accuracy of detect DoS attack is 90 % in three Experimental NSL KDD dataset by select 10 fea-ture only.

Evidential reasoning research on intrusion detection

Science.gov (United States)

Wang, Xianpei; Xu, Hua; Zheng, Sheng; Cheng, Anyu

2003-09-01

In this paper, we mainly aim at D-S theory of evidence and the network intrusion detection these two fields. It discusses the method how to apply this probable reasoning as an AI technology to the Intrusion Detection System (IDS). This paper establishes the application model, describes the new mechanism of reasoning and decision-making and analyses how to implement the model based on the synscan activities detection on the network. The results suggest that if only rational probability values were assigned at the beginning, the engine can, according to the rules of evidence combination and hierarchical reasoning, compute the values of belief and finally inform the administrators of the qualities of the traced activities -- intrusions, normal activities or abnormal activities.

Farming System Evolution and Adaptive Capacity: Insights for Adaptation Support

Directory of Open Access Journals (Sweden)

Jami L. Dixon

2014-02-01

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

Evaluation of Hanford Single-Shell Waste Tanks Suspected of Water Intrusion

International Nuclear Information System (INIS)

Feero, Amie J.; Washenfelder, Dennis J.; Johnson, Jeremy M.; Schofield, John S.

2013-01-01

Intrusions evaluations for twelve single-shell tanks were completed in 2013. The evaluations consisted of remote visual inspections, data analysis, and calculations of estimated intrusion rates. The observation of an intrusion or the preponderance of evidence confirmed that six of the twelve tanks evaluated had intrusions. These tanks were tanks 241-A-103, BX-101, BX-103, BX-110, BY-102, and SX-106

The potential for health risks from intrusion of contaminants into the distribution system from pressure transients.

Science.gov (United States)

LeChevallier, Mark W; Gullick, Richard W; Karim, Mohammad R; Friedman, Melinda; Funk, James E

2003-03-01

The potential for public health risks associated with intrusion of contaminants into water supply distribution systems resulting from transient low or negative pressures is assessed. It is shown that transient pressure events occur in distribution systems; that during these negative pressure events pipeline leaks provide a potential portal for entry of groundwater into treated drinking water; and that faecal indicators and culturable human viruses are present in the soil and water exterior to the distribution system. To date, all observed negative pressure events have been related to power outages or other pump shutdowns. Although there are insufficient data to indicate whether pressure transients are a substantial source of risk to water quality in the distribution system, mitigation techniques can be implemented, principally the maintenance of an effective disinfectant residual throughout the distribution system, leak control, redesign of air relief venting, and more rigorous application of existing engineering standards. Use of high-speed pressure data loggers and surge modelling may have some merit, but more research is needed.

Petroleum Vapor Intrusion

Science.gov (United States)

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

Active Low Intrusion Hybrid Monitor for Wireless Sensor Networks.

Science.gov (United States)

Navia, Marlon; Campelo, Jose C; Bonastre, Alberto; Ors, Rafael; Capella, Juan V; Serrano, Juan J

2015-09-18

Several systems have been proposed to monitor wireless sensor networks (WSN). These systems may be active (causing a high degree of intrusion) or passive (low observability inside the nodes). This paper presents the implementation of an active hybrid (hardware and software) monitor with low intrusion. It is based on the addition to the sensor node of a monitor node (hardware part) which, through a standard interface, is able to receive the monitoring information sent by a piece of software executed in the sensor node. The intrusion on time, code, and energy caused in the sensor nodes by the monitor is evaluated as a function of data size and the interface used. Then different interfaces, commonly available in sensor nodes, are evaluated: serial transmission (USART), serial peripheral interface (SPI), and parallel. The proposed hybrid monitor provides highly detailed information, barely disturbed by the measurement tool (interference), about the behavior of the WSN that may be used to evaluate many properties such as performance, dependability, security, etc. Monitor nodes are self-powered and may be removed after the monitoring campaign to be reused in other campaigns and/or WSNs. No other hardware-independent monitoring platforms with such low interference have been found in the literature.

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

Science.gov (United States)

Hernandez, B. C. B.

2015-12-01

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

Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Young-Jae Song

2009-07-01

Full Text Available Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.

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

International Nuclear Information System (INIS)

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

1985-01-01

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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. (low temperature plasma)

Railway clearance intrusion detection method with binocular stereo vision

Science.gov (United States)

Zhou, Xingfang; Guo, Baoqing; Wei, Wei

2018-03-01

In the stage of railway construction and operation, objects intruding railway clearance greatly threaten the safety of railway operation. Real-time intrusion detection is of great importance. For the shortcomings of depth insensitive and shadow interference of single image method, an intrusion detection method with binocular stereo vision is proposed to reconstruct the 3D scene for locating the objects and judging clearance intrusion. The binocular cameras are calibrated with Zhang Zhengyou's method. In order to improve the 3D reconstruction speed, a suspicious region is firstly determined by background difference method of a single camera's image sequences. The image rectification, stereo matching and 3D reconstruction process are only executed when there is a suspicious region. A transformation matrix from Camera Coordinate System(CCS) to Track Coordinate System(TCS) is computed with gauge constant and used to transfer the 3D point clouds into the TCS, then the 3D point clouds are used to calculate the object position and intrusion in TCS. The experiments in railway scene show that the position precision is better than 10mm. It is an effective way for clearance intrusion detection and can satisfy the requirement of railway application.

Specifying the Neurobiological Basis of Human Attachment: Brain, Hormones, and Behavior in Synchronous and Intrusive Mothers

Science.gov (United States)

Atzil, Shir; Hendler, Talma; Feldman, Ruth

2011-01-01

The mother–infant bond provides the foundation for the infant's future mental health and adaptation and depends on the provision of species-typical maternal behaviors that are supported by neuroendocrine and motivation-affective neural systems. Animal research has demonstrated that natural variations in patterns of maternal care chart discrete profiles of maternal brain–behavior relationships that uniquely shape the infant's lifetime capacities for stress regulation and social affiliation. Such patterns of maternal care are mediated by the neuropeptide Oxytocin and by stress- and reward-related neural systems. Human studies have similarly shown that maternal synchrony—the coordination of maternal behavior with infant signals—and intrusiveness—the excessive expression of maternal behavior—describe distinct and stable maternal styles that bear long-term consequences for infant well-being. To integrate brain, hormones, and behavior in the study of maternal–infant bonding, we examined the fMRI responses of synchronous vs intrusive mothers to dynamic, ecologically valid infant videos and their correlations with plasma Oxytocin. In all, 23 mothers were videotaped at home interacting with their infants and plasma OT assayed. Sessions were micro-coded for synchrony and intrusiveness. Mothers were scanned while observing several own and standard infant-related vignettes. Synchronous mothers showed greater activations in the left nucleus accumbens (NAcc) and intrusive mothers exhibited higher activations in the right amygdala. Functional connectivity analysis revealed that among synchronous mothers, left NAcc and right amygdala were functionally correlated with emotion modulation, theory-of-mind, and empathy networks. Among intrusive mothers, left NAcc and right amygdala were functionally correlated with pro-action areas. Sorting points into neighborhood (SPIN) analysis demonstrated that in the synchronous group, left NAcc and right amygdala activations showed

Pukala intrusion, its age and connection to hydrothermal alteration in Orivesi, southwestern Finland

Directory of Open Access Journals (Sweden)

Matti Talikka

2005-01-01

Full Text Available The Pukala intrusion is situated in the Paleoproterozoic Svecofennian domain of the Fennoscandian Shield in the contact region between the Central Finland Granitoid Complex and the Tampere Belt. The acid subvolcanic intrusion, which is in contact or close to severalaltered domains, mainly consists of porphyritic granodiorite and trondhjemite. The Pukala intrusion was emplaced into volcanic sequence in an island-arc or fore-arc setting before or during the early stages of the main regional deformation phase of the Svecofennian orogeny. On the basis of the geochemical data, the Pukala intrusion is a peraluminous volcanic-arc granitoid. After crystallisation at 1896±3 Ma, multiphase deformation and metamorphismcaused alteration, recrystallisation, and orientation of the minerals, and tilted the intrusion steeply towards south. The 1851±5 Ma U-Pb age for titanite is connected to the late stages of the Svecofennian tectonometamorphic evolution of the region. Several hydrothermally altered domains are located in the felsic and intermediate metavolcanic rocks of the Tampere Belt within less than one kilometre south of the Pukala intrusion. Alteration is divided into three basic types: partial silica alteration, chlorite-sericite±silica alteration, and sericite alteration in shear zones. The first two types probably formed during the emplacement and crystallisation of the Pukala intrusion, and the third is linked to late shearing. Intense sericitisation and comb quartz bands in the contact of theintrusion and the altered domain at Kutemajärvi suggest that the hydrothermal system was driven by the Pukala intrusion.

A novel intrusion detection method based on OCSVM and K-means recursive clustering

Directory of Open Access Journals (Sweden)

Leandros A. Maglaras

2015-01-01

Full Text Available In this paper we present an intrusion detection module capable of detecting malicious network traffic in a SCADA (Supervisory Control and Data Acquisition system, based on the combination of One-Class Support Vector Machine (OCSVM with RBF kernel and recursive k-means clustering. Important parameters of OCSVM, such as Gaussian width o and parameter v affect the performance of the classifier. Tuning of these parameters is of great importance in order to avoid false positives and over fitting. The combination of OCSVM with recursive k- means clustering leads the proposed intrusion detection module to distinguish real alarms from possible attacks regardless of the values of parameters o and v, making it ideal for real-time intrusion detection mechanisms for SCADA systems. Extensive simulations have been conducted with datasets extracted from small and medium sized HTB SCADA testbeds, in order to compare the accuracy, false alarm rate and execution time against the base line OCSVM method.

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

Science.gov (United States)

Husar, R. B.; Hoijarvi, K.

2017-12-01

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

Assessing Human Activity in Elderly People Using Non-Intrusive Load Monitoring.

Science.gov (United States)

Alcalá, José M; Ureña, Jesús; Hernández, Álvaro; Gualda, David

2017-02-11

The ageing of the population, and their increasing wish of living independently, are motivating the development of welfare and healthcare models. Existing approaches based on the direct heath-monitoring using body sensor networks (BSN) are precise and accurate. Nonetheless, their intrusiveness causes non-acceptance. New approaches seek the indirect monitoring through monitoring activities of daily living (ADLs), which proves to be a suitable solution. ADL monitoring systems use many heterogeneous sensors, are less intrusive, and are less expensive than BSN, however, the deployment and maintenance of wireless sensor networks (WSN) prevent them from a widespread acceptance. In this work, a novel technique to monitor the human activity, based on non-intrusive load monitoring (NILM), is presented. The proposal uses only smart meter data, which leads to minimum intrusiveness and a potential massive deployment at minimal cost. This could be the key to develop sustainable healthcare models for smart homes, capable of complying with the elderly people' demands. This study also uses the Dempster-Shafer theory to provide a daily score of normality with regard to the regular behavior. This approach has been evaluated using real datasets and, additionally, a benchmarking against a Gaussian mixture model approach is presented.

A Database of Computer Attacks for the Evaluation of Intrusion Detection Systems

Science.gov (United States)

1999-06-01

administrator whenever a system binary file (such as the ps, login , or ls program) is modified. Normal users have no legitimate reason to alter these files...development of EMERALD [46], which combines statistical anomaly detection from NIDES with signature verification. Specification-based intrusion detection...the creation of a single host that can act as many hosts. Daemons that provide network services—including telnetd, ftpd, and login — display banners

Water System Adaptation To Hydrological Changes: Module 12, Models and Tools for Stormwater and Wastewater System Adaptation

Science.gov (United States)

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

Research on intrusion detection based on Kohonen network and support vector machine

Science.gov (United States)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

In view of the problem of low detection accuracy and the long detection time of support vector machine, which directly applied to the network intrusion detection system. Optimization of SVM parameters can greatly improve the detection accuracy, but it can not be applied to high-speed network because of the long detection time. a method based on Kohonen neural network feature selection is proposed to reduce the optimization time of support vector machine parameters. Firstly, this paper is to calculate the weights of the KDD99 network intrusion data by Kohonen network and select feature by weight. Then, after the feature selection is completed, genetic algorithm (GA) and grid search method are used for parameter optimization to find the appropriate parameters and classify them by support vector machines. By comparing experiments, it is concluded that feature selection can reduce the time of parameter optimization, which has little influence on the accuracy of classification. The experiments suggest that the support vector machine can be used in the network intrusion detection system and reduce the missing rate.

Stress reaction process-based hierarchical recognition algorithm for continuous intrusion events in optical fiber prewarning system

Science.gov (United States)

Qu, Hongquan; Yuan, Shijiao; Wang, Yanping; Yang, Dan

2018-04-01

To improve the recognition performance of optical fiber prewarning system (OFPS), this study proposed a hierarchical recognition algorithm (HRA). Compared with traditional methods, which employ only a complex algorithm that includes multiple extracted features and complex classifiers to increase the recognition rate with a considerable decrease in recognition speed, HRA takes advantage of the continuity of intrusion events, thereby creating a staged recognition flow inspired by stress reaction. HRA is expected to achieve high-level recognition accuracy with less time consumption. First, this work analyzed the continuity of intrusion events and then presented the algorithm based on the mechanism of stress reaction. Finally, it verified the time consumption through theoretical analysis and experiments, and the recognition accuracy was obtained through experiments. Experiment results show that the processing speed of HRA is 3.3 times faster than that of a traditional complicated algorithm and has a similar recognition rate of 98%. The study is of great significance to fast intrusion event recognition in OFPS.

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

Science.gov (United States)

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

Attack Pattern Analysis Framework for a Multiagent Intrusion Detection System

Directory of Open Access Journals (Sweden)

Krzysztof Juszczyszyn

2008-08-01

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

Count out your intrusions: Effects of verbal encoding on intrusive memories

NARCIS (Netherlands)

Krans, J.; Näring, G.W.B.; Becker, E.S.

2009-01-01

Peri-traumatic information processing is thought to affect the development of intrusive trauma memories. This study aimed to replicate and improve the study by Holmes, Brewin, and Hennessy (2004, Exp. 3) on the role of peri-traumatic verbal processing in analogue traumatic intrusion development.

Options for human intrusion

International Nuclear Information System (INIS)

Bauser, M.; Williams, R.

1993-01-01

This paper addresses options for dealing with human intrusion in terms of performance requirements and repository siting and design requirements. Options are presented, along with the advantages and disadvantages of certain approaches. At the conclusion, a conceptual approach is offered emphasizing both the minimization of subjective judgements concerning future human activity, and specification of repository requirements to minimize the likelihood of human intrusion and any resulting, harmful effects should intrusion occur

Aspects of cold intrusions over Greece during autumn

Science.gov (United States)

Mita, Constantina; Marinaki, Aggeliki; Zeini, Konstantina; Konstantara, Metaxia

2010-05-01

This study is focused on the description of atmospheric disturbances that caused intense cold intrusions over Greece during autumn for a period of 25 years (1982-2006). The study was based on data analysis from the meteorological station network of the Hellenic National Meteorological Service (HNMS) and the European Centre for Medium Range Weather Forecasts (ECMWF). Initially, the days with temperature at the isobaric surface of 850 hPa less or equal to the mean temperature for the 10-day period the day under investigation belongs to are isolated, composing a new confined data set which was further used. An event of intense cold intrusion is identified based on a subjective set of criteria, considering the temperature decrease at the level of 850 hPa and its duration. In particular, the criteria that were used to identify a cold intrusion were: temperature variation between two successive days at the isobaric level of 850 hPa being equal or greater than 50 C at least once during the event and duration of the event of at least two successive days with continuous temperature decrease. Additionally, the synoptic analysis of the atmospheric disturbances involved using weather charts from ECMWF, revealed that all cases were related to low pressure systems at the level of 500 hPa, accompanied by cold air masses. Moreover, a methodology proposed to classify the cold intrusions based on general circulation characteristics of the atmosphere, resulted in seven major categories. More than half of the events belong in two categories, originated northwest of the greater Greek area (Greece and parts of neighbouring countries), between 400 and 600 N. Further analysis indicated that the frequency of events increases from September to November and the majority of the events lasted two to three days. Additionally, the non-parametric Mann-Kendall test was used for the investigation of the statistical significance of the trends appearing in the results. The tests revealed that over

Coplanar capacitance sensors for detecting water intrusion in composite structures

International Nuclear Information System (INIS)

Nassr, Amr A; El-Dakhakhni, Wael W; Ahmed, Wael H

2008-01-01

Composite materials are becoming more affordable and widely used for retrofitting, rehabilitating and repairing reinforced concrete structures designed and constructed under older specifications. However, the mechanical properties and long-term durability of composite materials may degrade severely in the presence of water intrusion. This study presents a new non-destructive evaluation (NDE) technique for detecting the water intrusion in composite structures by evaluating the dielectric properties of different composite system constituent materials. The variation in the dielectric signatures was employed to design a coplanar capacitance sensor with high sensitivity to detect such defects. An analytical model was used to study the effect of the sensor geometry on the output signal and to optimize sensor design. A finite element model was developed to validate analytical results and to evaluate other sensor design-related parameters. Experimental testing of a concrete specimen wrapped with composite laminate and containing a series of pre-induced water intrusion defects was conducted in order to validate the concept of the new technique. Experimental data showed excellent agreement with the finite element model predictions and confirmed sensor performance

Capability for intrusion detection at nuclear fuel sites

International Nuclear Information System (INIS)

1978-03-01

A safeguards vulnerability assessment was conducted at three separate licensed nuclear processing facilities. Emphasis was placed on: (1) performance of the total intrusion detection system, and (2) vulnerability of the system to compromise by insiders. The security guards were interviewed to evaluate their effectiveness in executing their duties in accordance with the plant's security plan and to assess their knowledge regarding the operation of the security equipment. A review of the training schedule showed that the guards, along with the other plant employees, are required to periodically attend in-plant training sessions. The vulnerability assessments continued with interviews of the personnel responsible for maintaining the security equipment, with discussions of detector false alarm and maintenance problems. The second part of the vulnerability assessments was to evaluate the effectiveness of the intrusion detection systems including the interior and the perimeter sensors, CCTV surveillance devices and the exterior lighting. Two types of perimeter detectors are used at the sites, a fence disturbance sensor and an infrared barrier type detector. Infrared barrier type detectors have a higher probability of detection, especially in conjunction with dedicated CCTV cameras. The exterior lights satisfy the 0.2 footcandle illumination requirement. The interior intrusion detection systems included ultrasonic motion detectors, microwave motion detectors,balanced magnetic switches, and CCTV cameras. Entrance doors to the materials access areas and vital areas are protected with balanced magnetic switches. The interior intrusion detection systems at the three nuclear processing sites are considered satisfactory with the exception of the areas protected with ultrasonic motion detectors

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

KAUST Repository

Zhang, Xiangliang; Wang, Wei

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

Provide a model to improve the performance of intrusion detection systems in the cloud

OpenAIRE

Foroogh Sedighi

2016-01-01

High availability of tools and service providers in cloud computing and the fact that cloud computing services are provided by internet and deal with public, have caused important challenges for new computing model. Cloud computing faces problems and challenges such as user privacy, data security, data ownership, availability of services, and recovery after breaking down, performance, scalability, programmability. So far, many different methods are presented for detection of intrusion in clou...

The Adaptive Multi-scale Simulation Infrastructure

Energy Technology Data Exchange (ETDEWEB)

Tobin, William R. [Rensselaer Polytechnic Inst., Troy, NY (United States)

2015-09-01

The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.

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

Science.gov (United States)

Prinos, Scott T.

2013-01-01

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

Complex Environmental Data Modelling Using Adaptive General Regression Neural Networks

Science.gov (United States)

Kanevski, Mikhail

2015-04-01

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

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

NARCIS (Netherlands)

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

2017-01-01

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

Assessing Human Activity in Elderly People Using Non-Intrusive Load Monitoring

Directory of Open Access Journals (Sweden)

José M. Alcalá

2017-02-01

Full Text Available The ageing of the population, and their increasing wish of living independently, are motivating the development of welfare and healthcare models. Existing approaches based on the direct heath-monitoring using body sensor networks (BSN are precise and accurate. Nonetheless, their intrusiveness causes non-acceptance. New approaches seek the indirect monitoring through monitoring activities of daily living (ADLs, which proves to be a suitable solution. ADL monitoring systems use many heterogeneous sensors, are less intrusive, and are less expensive than BSN, however, the deployment and maintenance of wireless sensor networks (WSN prevent them from a widespread acceptance. In this work, a novel technique to monitor the human activity, based on non-intrusive load monitoring (NILM, is presented. The proposal uses only smart meter data, which leads to minimum intrusiveness and a potential massive deployment at minimal cost. This could be the key to develop sustainable healthcare models for smart homes, capable of complying with the elderly people’ demands. This study also uses the Dempster-Shafer theory to provide a daily score of normality with regard to the regular behavior. This approach has been evaluated using real datasets and, additionally, a benchmarking against a Gaussian mixture model approach is presented.

Prospective relations between intrusive parenting and child behavior problems: Differential moderation by parasympathetic nervous system regulation and child sex.

Science.gov (United States)

Rudd, Kristen L; Alkon, Abbey; Yates, Tuppett M

2017-10-15

This study examined children's parasympathetic nervous system (PNS) regulation, which was indexed by respiratory sinus arrhythmia (RSA) during rest, reactivity, and recovery episodes, and sex as moderators of predicted relations between observed intrusive parenting and later observer-rated child behavior problems. Child-caregiver dyads (N=250; 50% girls; 46% Latino/a) completed a series of laboratory assessments yielding independent measures of intrusive parenting at age 4, PNS regulation at age 6, and child behavior problems at age 8. Results indicated that intrusive parenting was related to more internalizing problems among boys who showed low RSA reactivity (i.e., PNS withdrawal from pre-startle to startle challenge), but RSA reactivity did not moderate this relation among girls. Interestingly, RSA recovery (i.e., PNS activation from startle challenge to post-startle) moderated these relations differently for boys and girls. For girls with relatively low RSA post-startle (i.e., less recovery), intrusive parenting was positively related to both internalizing and externalizing problems. However, the reverse was true for boys, such that there was a significant positive relation between intrusive parenting and later externalizing problems among boys who evidenced relatively high RSA post-startle (i.e., more recovery). Findings provide evidence for the moderation of intrusive caregiving effects by children's PNS regulation while highlighting the differential patterning of these relations across distinct phases of the regulatory response and as a function of child sex. Copyright © 2017 Elsevier Inc. All rights reserved.

Data acquisition and test system software

International Nuclear Information System (INIS)

Bourgeois, N.A. Jr.

1979-03-01

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

Multisensor Fusion for Intrusion Detection and Situational Awareness

OpenAIRE

Hallstensen, Christoffer V

2017-01-01

Cybercrime damage costs the world several trillion dollars annually. And al-though technical solutions to protect organizations from hackers are being con-tinuously developed, criminals learn fast to circumvent them. The question is,therefore, how to create leverage to protect an organization by improving in-trusion detection and situational awareness? This thesis seeks to contribute tothe prior art in intrusion detection and situational awareness by using a multi-sensor data fusion...

The evolution of Interior Intrusion Detection Technology at Sandia National Laboratories

International Nuclear Information System (INIS)

Graham, R.H.; Workhoven, R.M.

1987-07-01

Interior Intrusion Detection Technology began at Sandia National Laboratories (SNL) in 1975 as part of the Fixed Facilities Physical Protection Research and Development program sponsored by the US Department of Energy in connection with their nuclear safeguards effort. This paper describes the evolution of Interior Intrusion Detection Technology at Sandia National Laboratories from the beginning of the Interior Sensor Laboratory to the present. This Laboratory was established in 1976 to evaluate commercial interior intrusion sensors and to assist in site-specific intrusion detection system designs. Examples of special test techniques and new test equipment that were developed at the Lab are presented, including the Sandia Intruder Motion Simulator (SIMS), the Sensor and Environment Monitor (SEM), and the Sandia Interior Robot (SIR). We also discuss new sensors and unique sensor combinations developed when commercial sensors were unavailable and the future application of expert systems

Data-driven adaptive fractional order PI control for PMSM servo system with measurement noise and data dropouts.

Science.gov (United States)

Xie, Yuanlong; Tang, Xiaoqi; Song, Bao; Zhou, Xiangdong; Guo, Yixuan

2018-04-01

In this paper, data-driven adaptive fractional order proportional integral (AFOPI) control is presented for permanent magnet synchronous motor (PMSM) servo system perturbed by measurement noise and data dropouts. The proposed method directly exploits the closed-loop process data for the AFOPI controller design under unknown noise distribution and data missing probability. Firstly, the proposed method constructs the AFOPI controller tuning problem as a parameter identification problem using the modified l p norm virtual reference feedback tuning (VRFT). Then, iteratively reweighted least squares is integrated into the l p norm VRFT to give a consistent compensation solution for the AFOPI controller. The measurement noise and data dropouts are estimated and eliminated by feedback compensation periodically, so that the AFOPI controller is updated online to accommodate the time-varying operating conditions. Moreover, the convergence and stability are guaranteed by mathematical analysis. Finally, the effectiveness of the proposed method is demonstrated both on simulations and experiments implemented on a practical PMSM servo system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

How Intrusion Detection Can Improve Software Decoy Applications

National Research Council Canada - National Science Library

Monteiro, Valter

2003-01-01

This research concerns information security and computer-network defense. It addresses how to handle the information of log files and intrusion-detection systems to recognize when a system is under attack...

Water System Adaptation To Hydrological Changes: Module 14, Life Cycle Analysis (LCA) and Prioritization Tools in Water System Adaptation

Science.gov (United States)

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

Evaluation of of μ-controller PIR Intrusion Detector | Eludire | West ...

African Journals Online (AJOL)

When there is intrusion, a piezo speaker beeps and also a visual indicator with light emitting diode blinks to indicate intrusion. For security, cost effectiveness and access control to certain areas of homes, offices and industries this system is a better replacement to human surveillance needed around our valuable goods and ...

The evolution of interior intrusion detection technology at Sandia National Laboratories

International Nuclear Information System (INIS)

Graham, R.H.; Workhoven, R.M.

1987-07-01

Interior Intrusion Detection Technology began at Sandia National Laboratories (SNL) in 1975 as part of the Fixed Facilities Physical Protection Research and Development program sponsored by the US Department of Energy in connection with their nuclear safeguards effort. This paper describes the evolution of Interior Intrusion Detection Technology at Sandia National Laboratories from the beginning of the Interior Sensor Laboratory to the present. This Laboratory was established in 1976 to evaluate commercial interior intrusion sensors and to assist in site-specific intrusion detection system designs. Examples of special test techniques and new test equipment that were developed at the Lab are presented, including the Sandia Intruder Motion Simulator (SIMS), the Sensor and Environment Monitor (SEM), and the Sandia Interior Robot (SIR). We also discuss new sensors and unique sensor combination developed when commercial sensors were unavailable and the future application of expert systems. 5 refs

The evolution of interior intrusion detection technology at Sandia National Laboratories

International Nuclear Information System (INIS)

Graham, R.H.; Workhoven, R.M.

1987-01-01

Interior Intrusion Detection Technology began at Sandia National Laboratories (SNL) in 1975 as part of the Fixed Facilities Physical Protection Research and Development program sponsored by the U.S. Department of Energy in connection with their nuclear safeguards effort. This paper describes the evolution of Interior Intrusion Detection Technology at Sandia National Laboratories from the beginning of the Interior Sensor Laboratory to the present. This Laboratory was established in 1976 to evaluate commercial interior intrusion sensors and to assist in site-specific intrusion detection system designs. Examples of special test techniques and new test equipment that were developed at the Lab are presented, including the Sandia Intruder Motion Simulator (SIMS), the Sensor and Environment Monitor (SEM), and the Sandia Interior Robot (SIR). The authors also discuss new sensors and unique sensor combinations developed when commercial sensors were unavailable and the future application of expert systems

Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

Science.gov (United States)

Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

2017-10-01

The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

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

Directory of Open Access Journals (Sweden)

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.

Improved wavelet packet classification algorithm for vibrational intrusions in distributed fiber-optic monitoring systems

Science.gov (United States)

Wang, Bingjie; Pi, Shaohua; Sun, Qi; Jia, Bo

2015-05-01

An improved classification algorithm that considers multiscale wavelet packet Shannon entropy is proposed. Decomposition coefficients at all levels are obtained to build the initial Shannon entropy feature vector. After subtracting the Shannon entropy map of the background signal, components of the strongest discriminating power in the initial feature vector are picked out to rebuild the Shannon entropy feature vector, which is transferred to radial basis function (RBF) neural network for classification. Four types of man-made vibrational intrusion signals are recorded based on a modified Sagnac interferometer. The performance of the improved classification algorithm has been evaluated by the classification experiments via RBF neural network under different diffusion coefficients. An 85% classification accuracy rate is achieved, which is higher than the other common algorithms. The classification results show that this improved classification algorithm can be used to classify vibrational intrusion signals in an automatic real-time monitoring system.

Perimeter intrusion sensors

International Nuclear Information System (INIS)

Eaton, M.J.

1977-01-01

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

Adaptation in Living Systems

Science.gov (United States)

Tu, Yuhai; Rappel, Wouter-Jan

2018-03-01

Adaptation refers to the biological phenomenon where living systems change their internal states in response to changes in their environments in order to maintain certain key functions critical for their survival and fitness. Adaptation is one of the most ubiquitous and arguably one of the most fundamental properties of living systems. It occurs throughout all biological scales, from adaptation of populations of species over evolutionary time to adaptation of a single cell to different environmental stresses during its life span. In this article, we review some of the recent progress made in understanding molecular mechanisms of cellular-level adaptation. We take the minimalist (or the physicist) approach and study the simplest systems that exhibit generic adaptive behaviors, namely chemotaxis in bacterium cells (Escherichia coli) and eukaryotic cells (Dictyostelium). We focus on understanding the basic biochemical interaction networks that are responsible for adaptation dynamics. By combining theoretical modeling with quantitative experimentation, we demonstrate universal features in adaptation as well as important differences in different cellular systems. Future work in extending the modeling framework to study adaptation in more complex systems such as sensory neurons is also discussed.

Effects of climate variability on saltwater intrusions in coastal aquifers in Southern Denmark

Science.gov (United States)

Meyer, Rena; Sonnenborg, Torben; Engesgaard, Peter; Høyer, Anne-Sophie; Jørgensen, Flemming; Hisnby, Klaus; Hansen, Birgitte; Jensen, Jørn Bo; Piotrowski, Jan A.

2016-04-01

study shows how hydrogeological, geophysical and geochemical data can be complementarily used together with groundwater flow and transport simulations to understand the history of the groundwater systems and thus help adapting water resources to future changes.

Assessment of permeation quality of concrete through mercury intrusion porosimetry

International Nuclear Information System (INIS)

Kumar, Rakesh; Bhattacharjee, B.

2004-01-01

Permeation quality of laboratory cast concrete beams was determined through initial surface absorption test (ISAT). The pore system characteristics of the same concrete beam specimens were determined through mercury intrusion porosimetry (MIP). Data so obtained on the measured initial surface absorption rate of water by concrete and characteristics of pore system of concrete estimated from porosimetry results were used to develop correlations between them. Through these correlations, potential of MIP in assessing the durability quality of concrete in actual structure is demonstrated

Dynamic and adaptive data-management in ATLAS

CERN Document Server

Lassnig, M; Branco, M; Molfetas, A

2010-01-01

Distributed data-management on the grid is subject to huge uncertainties yet static policies govern its usage. Due to the unpredictability of user behaviour, the high-latency and the heterogeneous nature of the environment, distributed data-management on the grid is challenging. In this paper we present the first steps towards a future dynamic data-management system that adapts to the changing conditions and environment. Such a system would eliminate the number of manual interventions and remove unnecessary software layers, thereby providing a higher quality of service to the collaboration.

Igneous Intrusion Impacts on Waste Packages and Waste Forms

International Nuclear Information System (INIS)

P. Bernot

2004-01-01

The purpose of this model report is to assess the potential impacts of igneous intrusion on waste packages and waste forms in the emplacement drifts at the Yucca Mountain Repository. The model is based on conceptual models and includes an assessment of deleterious dynamic, thermal, hydrologic, and chemical impacts. This constitutes the waste package and waste form impacts submodel of the Total System Performance Assessment for the License Application (TSPA-LA) model assessing the impacts of a hypothetical igneous intrusion event on the repository total system performance. This submodel is carried out in accordance with Technical Work Plan for Waste Form Degradation Modeling, Testing, and Analyses in Support of SR and LA (BSC 2003a) and Total System Performance Assessment-License Application Methods and Approaches (BSC 2002a). The technical work plan is governed by the procedures of AP-SIII.10Q, Models. Any deviations from the technical work plan are documented in the TSPA-LA approach to implementing the models for waste package and waste form response during igneous intrusion is based on identification of damage zones. Zone 1 includes all emplacement drifts intruded by the basalt dike, and Zone 2 includes all other emplacement drifts in the repository that are not in Zone 1. This model report will document the following model: (1) Impacts of magma intrusion on the components of engineered barrier system (e.g., drip shields and cladding) of emplacement drifts in Zone 1, and the fate of waste forms. (2) Impacts of conducting magma heat and diffusing magma gases on the drip shields, waste packages, and cladding in the Zone 2 emplacement drifts adjacent to the intruded drifts. (3) Impacts of intrusion on Zone 1 in-drift thermal and geochemical environments, including seepage hydrochemistry. The scope of this model only includes impacts to the components stated above, and does not include impacts to other engineered barrier system (EBS) components such as the invert and

Igneous Intrusion Impacts on Waste Packages and Waste Forms

Energy Technology Data Exchange (ETDEWEB)

P. Bernot

2004-08-16

The purpose of this model report is to assess the potential impacts of igneous intrusion on waste packages and waste forms in the emplacement drifts at the Yucca Mountain Repository. The model is based on conceptual models and includes an assessment of deleterious dynamic, thermal, hydrologic, and chemical impacts. This constitutes the waste package and waste form impacts submodel of the Total System Performance Assessment for the License Application (TSPA-LA) model assessing the impacts of a hypothetical igneous intrusion event on the repository total system performance. This submodel is carried out in accordance with Technical Work Plan for Waste Form Degradation Modeling, Testing, and Analyses in Support of SR and LA (BSC 2003a) and Total System Performance Assessment-License Application Methods and Approaches (BSC 2002a). The technical work plan is governed by the procedures of AP-SIII.10Q, Models. Any deviations from the technical work plan are documented in the TSPA-LA approach to implementing the models for waste package and waste form response during igneous intrusion is based on identification of damage zones. Zone 1 includes all emplacement drifts intruded by the basalt dike, and Zone 2 includes all other emplacement drifts in the repository that are not in Zone 1. This model report will document the following model: (1) Impacts of magma intrusion on the components of engineered barrier system (e.g., drip shields and cladding) of emplacement drifts in Zone 1, and the fate of waste forms. (2) Impacts of conducting magma heat and diffusing magma gases on the drip shields, waste packages, and cladding in the Zone 2 emplacement drifts adjacent to the intruded drifts. (3) Impacts of intrusion on Zone 1 in-drift thermal and geochemical environments, including seepage hydrochemistry. The scope of this model only includes impacts to the components stated above, and does not include impacts to other engineered barrier system (EBS) components such as the invert and

Joint Adaptive Modulation and Combining for Hybrid FSO/RF Systems

KAUST Repository

Rakia, Tamer

2015-11-12

In this paper, we present and analyze a new transmission scheme for hybrid FSO/RF communication system based on joint adaptive modulation and adaptive combining. Specifically, the data rate on the FSO link is adjusted in discrete manner according to the FSO link\\'s instantaneous received signal-to-noise-ratio (SNR). If the FSO link\\'s quality is too poor to maintain the target bit-error-rate, the system activates the RF link along with the FSO link. When the RF link is activated, simultaneous transmission of the same modulated data takes place on both links, where the received signals from both links are combined using maximal ratio combining scheme. In this case, the data rate of the system is adjusted according to the instantaneous combined SNRs. Novel analytical expression for the cumulative distribution function (CDF) of the received SNR for the proposed adaptive hybrid system is obtained. This CDF expression is used to study the spectral and outage performances of the proposed adaptive hybrid FSO/RF system. Numerical examples are presented to compare the performance of the proposed adaptive hybrid FSO/RF system with that of switch-over hybrid FSO/RF and FSO-only systems employing the same adaptive modulation schemes. © 2015 IEEE.

Intrusive luxation of 60 permanent incisors

DEFF Research Database (Denmark)

Tsilingaridis, Georgios; Malmgren, Barbro; Andreasen, Jens O

2012-01-01

  Intrusive luxation in the permanent dentition is an uncommon injury but it is considered one of the most severe types of dental trauma because of the risk for damage to the periodontal ligament, pulp and alveolar bone. Management of intrusive luxation in the permanent dentition is controversial....... The purpose of this study was to evaluate pulp survival and periodontal healing in intrusive luxated permanent teeth in relation to treatment alternatives, degree of intrusion and root development....

Boosting Web Intrusion Detection Systems by Inferring Positive Signatures

NARCIS (Netherlands)

Bolzoni, D.; Etalle, Sandro

2008-01-01

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

Information Quality Aware Data Collection for Adaptive Monitoring of Distribution Grids

DEFF Research Database (Denmark)

Kemal, Mohammed Seifu; Olsen, Rasmus Løvenstein; Schwefel, Hans-Peter

2017-01-01

frequency during run time. The data collection system should adapt to changing dynamics of the communication network and electrical grid. This paper first introduces adaptation functionalities for the data collection mechanism. To study and analyse the influence of configuration parameters that can......Abstract. Information from existing smart metering infrastructure, mainly used for billing purposes can also be utilised to monitor and control state of the grid. To add functionalities such as fault detection and real-time state estimation, data from smart meters should be accessed with increased...... be utilised for adaptation, a two-layer smart meter data access infrastructure is presented. An information quality metric, Mismatch Probability (mmPr) is introduced for the quantitative analysis of the two-layer data access system implemented in MATLAB based discrete event simulation study....

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

Directory of Open Access Journals (Sweden)

V. I. Shynkarenko

2016-04-01

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

Contributions of non-intrusive coupling in nonlinear structural mechanics

International Nuclear Information System (INIS)

Duval, Mickael

2016-01-01

This PhD thesis, part of the ANR ICARE project, aims at developing methods for complex analysis of large scale structures. The scientific challenge is to investigate very localised areas, but potentially critical as of mechanical systems resilience. Classically, representation models, discretizations, mechanical behaviour models and numerical tools are used at both global and local scales for simulation needs of graduated complexity. Global problem is handled by a generic code with topology (plate formulation, geometric approximation...) and behaviour (homogenization) simplifications while local analysis needs implementation of specialized tools (routines, dedicated codes) for an accurate representation of the geometry and behaviour. The main goal of this thesis is to develop an efficient non-intrusive coupling tool for multi-scale and multi-model structural analysis. Constraints of non-intrusiveness result in the non-modification of the stiffness operator, connectivity and the global model solver, allowing to work in a closed source software environment. First, we provide a detailed study of global/local non-intrusive coupling algorithm. Making use of several relevant examples (cracking, elastic-plastic behaviour, contact...), we show the efficiency and the flexibility of such coupling method. A comparative analysis of several optimisation tools is also carried on, and the interacting multiple patches situation is handled. Then, non-intrusive coupling is extended to globally non-linear cases, and a domain decomposition method with non-linear re-localization is proposed. Such methods allowed us to run a parallel computation using only sequential software, on a high performance computing cluster. Finally, we apply the coupling algorithm to mesh refinement with patches of finite elements. We develop an explicit residual based error estimator suitable for multi-scale solutions arising from the non-intrusive coupling, and apply it inside an error driven local mesh

Impact of a Saharan dust intrusion over southern Spain on DNI estimation with sky cameras

Science.gov (United States)

Alonso-Montesinos, J.; Barbero, J.; Polo, J.; López, G.; Ballestrín, J.; Batlles, F. J.

2017-12-01

To operate Central Tower Solar Power (CTSP) plants properly, solar collector systems must be able to work under varied weather conditions. Therefore, knowing the state of the atmosphere, and more specifically the level of incident radiation, is essential operational information to adapt the electricity production system to atmospheric conditions. In this work, we analyze the impact of a strong Saharan dust intrusion on the Direct normal irradiance (DNI) registered at two sites 35 km apart in southeastern Spain: the University of Almería (UAL) and the Plataforma Solar de Almería (PSA). DNI can be inputted into the European Solar Radiation Atlas (ESRA) clear sky procedure to derive Linke turbidity values, which proved to be extremely high at the UAL. By using the Simple Model of the Atmospheric Radiative Transfer of Sunshine (SMARTS) at the PSA site, AERONET data from PSA and assuming dust dominated aerosol, DNI estimations agreed strongly with the measured DNI values. At the UAL site, a SMARTS simulation of the DNI values also seemed to be compatible with dust dominated aerosol.

Perceived illness intrusion among patients on hemodialysis

International Nuclear Information System (INIS)

Bapat, Usha; Kedlaya, Prashanth G; Gokulnath

2009-01-01

Dialysis therapy is extremely stressful as it interferes with all spheres of daily activities of the patients. This study is aimed at understanding the perceived illness intrusion among patients on hemodialysis (HD) and to find the association between illness intrusion and patient demo-graphics as well as duration of dialysis. A cross sectional study involving 90 patients with chronic kidney disease (CKD) stage V, on HD was performed during the period from 2005 to 2006. The subjects included were above 18 years of age, willing, stable and on dialysis for at least two months. Patients with psychiatric co-morbidity were excluded. A semi-structured interview schedule covering sociodemographics and a 13 item illness intrusion checklist covering the various aspects of life was carried out. The study patients were asked to rate the illness intrusion and the extent. The data were analyzed statistically. The mean age of the subjects was 50.28 + - 13.69 years, males were predominant (85%), 73% were married, 50% belonged to Hindu religion, 25% had pre-degree education, 25% were employed and 22% were housewives. About 40% and 38% of the study patients belonged to middle and upper socio-economic strata respectively; 86% had urban background and lived in nuclear families. The mean duration on dialysis was 24 + - 29.6 months. All the subjects reported illness intrusion to a lesser or greater extent in various areas including: health (44%), work (70%) finance (55%), diet (50%) sexual life (38%) and psychological status (25%). Illness had not intruded in areas of relationship with spouse (67%), friends (76%), family (79%), social (40%) and religious functions (72%). Statistically significant association was noted between illness intrusion and occupation (P= 0.02). (author)

Perceived illness intrusion among patients on hemodialysis

Directory of Open Access Journals (Sweden)

Bapat Usha

2009-01-01

Full Text Available Dialysis therapy is extremely stressful as it interferes with all spheres of daily acti-vities of the patients. This study is aimed at understanding the perceived illness intrusion among pa-tients on hemodialysis (HD and to find the association between illness intrusion and patient demo-graphics as well as duration of dialysis. A cross sectional study involving 90 patients with chronic kidney disease (CKD stage V, on HD was performed during the period from 2005 to 2006. The subjects included were above 18 years of age, willing, stable and on dialysis for at least two months. Patients with psychiatric co-morbidity were excluded. A semi-structured interview schedule covering socio-demographics and a 13 item illness intrusion checklist covering the various aspects of life was ca-rried out. The study patients were asked to rate the illness intrusion and the extent. The data were ana-lyzed statistically. The mean age of the subjects was 50.28 ± 13.69 years, males were predominant (85%, 73% were married, 50% belonged to Hindu religion, 25% had pre-degree education, 25% were employed and 22% were housewives. About 40% and 38% of the study patients belonged to middle and upper socio-economic strata respectively; 86% had urban background and lived in nuclear fami-lies. The mean duration on dialysis was 24 ± 29.6 months. All the subjects reported illness intrusion to a lesser or greater extent in various areas including: health (44%, work (70% finance (55%, diet (50% sexual life (38% and psychological status (25%. Illness had not intruded in areas of rela-tionship with spouse (67%, friends (76%, family (79%, social (40% and religious functions (72%. Statistically significant association was noted between illness intrusion and occupation (P= 0.02.

Computational identification of adaptive mutants using the VERT system

Directory of Open Access Journals (Sweden)

Winkler James

2012-04-01

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

Linking precious metal enrichment and halogen cycling in mafic magmatic systems: insights from the Rum layered intrusion, NW Scotland

Science.gov (United States)

Kelly, A. P.; O'Driscoll, B.; Clay, P. L.; Burgess, R.

2017-12-01

Layered intrusions host the world's largest known concentrations of the platinum-group elements (PGE). Emphasis has been attached to the role of halogen-bearing fluids in concentrating the precious metals, but whether this occurs at the magmatic stage, or via subsequent metasomatism, is actively debated. One obstacle to progress has been the analytical difficulty of measuring low abundances of the halogens in the cumulate products of layered intrusions. To elucidate the importance of the halogens in facilitating PGE-mineralisation, as well as fingerprint halogen provenance and assess the importance of halogen cycling in mafic magma systems more generally, a suite of samples encompassing different stages of activity of the Palaeogene Rum layered intrusion was investigated. Halogen abundances were measured by neutron irradiation noble gas mass spectrometric analysis, permitting the detection of relatively low (ppm-ppb) abundances of Cl, Br and I in mg-sized samples. The samples include PGE-enriched chromite seams, various cumulates (e.g., peridotites), picrites (approximating the Rum parental magma), and pegmatites representing volatile-rich melts that circulated the intrusion at a late-stage in its solidification history. The new data reveal that PGE-bearing chromite seams contain relatively low Cl concentrations (2-3 ppm), with high molar ratios of Br/Cl and I/Cl (0.005 and 0.009, respectively). The picrites and cumulates have Br/Cl and I/Cl ratios close to sub-continental lithospheric mantle values of approximately 0.0013 and 0.00002, respectively, and thus likely reflect the Rum magma source region. A positive correlation between Cl and Br signifies comparable partitioning behaviour in all samples. However, I is more variable, displaying a positive correlation with Cl for more primitive samples (e.g. picrite and peridotite), and seemingly decoupling from Br and Cl in chromite seams and pegmatites. The relative enrichment of I over Cl in the chromite seams points

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

Science.gov (United States)

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

Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection

Directory of Open Access Journals (Sweden)

Jayakumar Kaliappan

2015-01-01

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

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

Science.gov (United States)

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

Using discriminant analysis to detect intrusions in external communication for self-driving vehicles

Directory of Open Access Journals (Sweden)

Khattab M.Ali Alheeti

2017-08-01

Full Text Available Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoc networks is crucial to the reliable exchange of information and control data. In this paper, we propose an intelligent Intrusion Detection System (IDS to protect the external communication of self-driving and semi self-driving vehicles. This technology has the ability to detect Denial of Service (DoS and black hole attacks on vehicular ad hoc networks (VANETs. The advantage of the proposed IDS over existing security systems is that it detects attacks before they causes significant damage. The intrusion prediction technique is based on Linear Discriminant Analysis (LDA and Quadratic Discriminant Analysis (QDA which are used to predict attacks based on observed vehicle behavior. We perform simulations using Network Simulator 2 to demonstrate that the IDS achieves a low rate of false alarms and high accuracy in detection.

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

Science.gov (United States)

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

2018-06-01

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

Non-intrusive uncertainty quantification in structural-acoustic systems using polynomial chaos expansion method

Directory of Open Access Journals (Sweden)

Wang Mingjie

2017-01-01

Full Text Available A framework of non-intrusive polynomial chaos expansion method (PC was proposed to investigate the statistic characteristics of the response of structural-acoustic system containing random uncertainty. The PC method does not need to reformulate model equations, and the statistics of the response can be evaluated directly. The results show that compared to the direct Monte Carlo method (MCM based on the original numerical model, the PC method is effective and more efficient.

A Survey on Cross-Layer Intrusion Detection System for Wireless ...

African Journals Online (AJOL)

pc

2018-03-05

Mar 5, 2018 ... excessive packet collision, artificially increases contention, decrease signal .... Intelligent security architecture was conducted by [36], as an intrusion ... the main disadvantages of this scheme is: The IDS node is static (runs ...

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

Directory of Open Access Journals (Sweden)

Vittorio Astarita

2017-01-01

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

[Analysis of intrusion errors in free recall].

Science.gov (United States)

Diesfeldt, H F A

2017-06-01

Extra-list intrusion errors during five trials of the eight-word list-learning task of the Amsterdam Dementia Screening Test (ADST) were investigated in 823 consecutive psychogeriatric patients (87.1% suffering from major neurocognitive disorder). Almost half of the participants (45.9%) produced one or more intrusion errors on the verbal recall test. Correct responses were lower when subjects made intrusion errors, but learning slopes did not differ between subjects who committed intrusion errors and those who did not so. Bivariate regression analyses revealed that participants who committed intrusion errors were more deficient on measures of eight-word recognition memory, delayed visual recognition and tests of executive control (the Behavioral Dyscontrol Scale and the ADST-Graphical Sequences as measures of response inhibition). Using hierarchical multiple regression, only free recall and delayed visual recognition retained an independent effect in the association with intrusion errors, such that deficient scores on tests of episodic memory were sufficient to explain the occurrence of intrusion errors. Measures of inhibitory control did not add significantly to the explanation of intrusion errors in free recall, which makes insufficient strength of memory traces rather than a primary deficit in inhibition the preferred account for intrusion errors in free recall.

Testing alternative conceptual models of seawater intrusion in a coastal aquifer using computer simulation, southern California, USA

Science.gov (United States)

Nishikawa, Tracy

1997-01-01

Two alternative conceptual models of the physical processes controlling seawater intrusion in a coastal basin in California, USA, were tested to identify a likely principal pathway for seawater intrusion. The conceptual models were tested by using a two-dimensional, finite-element groundwater flow and transport model. This pathway was identified by the conceptual model that best replicated the historical data. The numerical model was applied in cross section to a submarine canyon that is a main avenue for seawater to enter the aquifer system underlying the study area. Both models are characterized by a heterogeneous, layered, water-bearing aquifer. However, the first model is characterized by flat-lying aquifer layers and by a high value of hydraulic conductivity in the basal aquifer layer, which is thought to be a principal conduit for seawater intrusion. The second model is characterized by offshore folding, which was modeled as a very nearshore outcrop, thereby providing a shorter path for seawater to intrude. General conclusions are that: 1) the aquifer system is best modeled as a flat, heterogeneous, layered system; 2) relatively thin basal layers with relatively high values of hydraulic conductivity are the principal pathways for seawater intrusion; and 3) continuous clay layers of low hydraulic conductivity play an important role in controlling the movement of seawater.

Misuse and intrusion detection at Los Alamos National Laboratory

Energy Technology Data Exchange (ETDEWEB)

Jackson, K.A.; Neuman, M.C.; Simmonds, D.D.; Stallings, C.A.; Thompson, J.L.; Christoph, G.G.

1995-04-01

An effective method for detecting computer misuse is the automatic auditing and analysis of on-line user activity. This activity is reflected in system audit records, in system vulnerability postures, and in other evidence found through active system testing. Since 1989 we have implemented a misuse and intrusion detection system at Los Alamos. This is the Network Anomaly Detection and Intrusion Reporter, or NADIR. NADIR currently audits a Kerberos distributed authentication system, file activity on a mass, storage system, and four Cray supercomputers that run the UNICOS operating system. NADIR summarizes user activity and system configuration in statistical profiles. It compares these profiles to expert rules that define security policy and improper or suspicious behavior. It reports suspicious behavior to security auditors and provides tools to aid in follow-up investigations, As NADIR is constantly evolving, this paper reports its development to date.

Perceived illness intrusions among continuous ambulatory peritoneal dialysis patients

Directory of Open Access Journals (Sweden)

Usha Bapat

2012-01-01

Full Text Available To study the perceived illness intrusion of continuous ambulatory peritoneal dialysis (CAPD patients, to examine their demographics, and to find out the association among demographics, duration of illness as well as illness intrusion, 40 chronic kidney disease stage V patients on CAPD during 2006-2007 were studied. Inclusion criteria were patients′ above 18 years, willing, stable, and completed at least two months of dialysis. Those with psychiatric co-morbidity were excluded. Sociodemographics were collected using a semi-structured interview schedule. A 14-item illness intrusion checklist covering various aspects of life was administered. The subjects had to rate the illness intrusion in their daily life and the extent of intrusion. The data was analyzed using descriptive statistics and chi square test of association. The mean age of the subjects was 56.05 ± 10.05 years. There was near equal distribution of gender. 82.5% were married, 70.0% belonged to Hindu religion, 45.0% were pre-degree, 25.0% were employed, 37.5% were housewives and 30.0% had retired. 77.5% belonged to the upper socioeconomic strata, 95.0% were from an urban background and 65.0% were from nuclear families. The mean duration of dialysis was 19.0 ± 16.49 months. Fifty-eight percent of the respondents were performing the dialysis exchanges by themselves. More than 95.0%were on three or four exchanges per day. All the 40 subjects reported illness intrusion in their daily life. Intrusion was perceived to some extent in the following areas: health 47.5%, work 25.0%, finance 37.5%, diet 40.0%, and psychological 50.0%. Illness had not intruded in the areas of relationship with spouse 52.5%, sexual life 30.0%, with friends 92.5%, with family 85.5%, social functions 52.5%, and religious functions 75.0%. Statistically significant association was not noted between illness intrusion and other variables. CAPD patients perceived illness intrusion to some extent in their daily life

Modeling the influence of river discharge on salt intrusion and residual circulation in Danshuei River estuary, Taiwan

Science.gov (United States)

Liu, W.-C.; Chen, W.-B.; Cheng, R.T.; Hsu, M.-H.; Kuo, A.Y.

2007-01-01

A 3-D, time-dependent, baroclinic, hydrodynamic and salinity model was implemented and applied to the Danshuei River estuarine system and the adjacent coastal sea in Taiwan. The model forcing functions consist of tidal elevations along the open boundaries and freshwater inflows from the main stream and major tributaries in the Danshuei River estuarine system. The bottom friction coefficient was adjusted to achieve model calibration and verification in model simulations of barotropic and baroclinic flows. The turbulent diffusivities were ascertained through comparison of simulated salinity time series with observations. The model simulation results are in qualitative agreement with the available field data. The validated model was then used to investigate the influence of freshwater discharge on residual current and salinity intrusion under different freshwater inflow condition in the Danshuei River estuarine system. The model results reveal that the characteristic two-layered estuarine circulation prevails most of the time at Kuan-Du station near the river mouth. Comparing the estuarine circulation under low- and mean flow conditions, the circulation strengthens during low-flow period and its strength decreases at moderate river discharge. The river discharge is a dominating factor affecting the salinity intrusion in the estuarine system. A correlation between the distance of salt intrusion and freshwater discharge has been established allowing prediction of salt intrusion for different inflow conditions. ?? 2007 Elsevier Ltd. All rights reserved.

A Privacy-Preserving Framework for Collaborative Intrusion Detection Networks Through Fog Computing

DEFF Research Database (Denmark)

Wang, Yu; Xie, Lin; Li, Wenjuan

2017-01-01

Nowadays, cyber threats (e.g., intrusions) are distributed across various networks with the dispersed networking resources. Intrusion detection systems (IDSs) have already become an essential solution to defend against a large amount of attacks. With the development of cloud computing, a modern IDS...

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

Directory of Open Access Journals (Sweden)

Didit Suhartono

2015-02-01

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

Association between intrusive negative autobiographical memories and depression: A meta-analytic investigation.

Science.gov (United States)

Mihailova, Stella; Jobson, Laura

2018-02-23

The study investigated several associations between depression and intrusive negative autobiographical memories. A systematic literature search identified 23 eligible studies (N = 2,582), which provided 59 effect sizes. Separate meta-analyses indicated that depression was moderately, positively associated with intrusive memory frequency, memory distress, maladaptive memory appraisals, memory avoidance, and memory rumination. Intrusive memory vividness was not significantly associated with depression. There were insufficient data to examine the relationship between depression and memory vantage perspective. Between-study heterogeneity was high for intrusive memory frequency and memory avoidance, and the percentage of females in studies significantly moderated the relationship between these variables and depression. An additional exploratory meta-analysis (3 studies; N = 257) indicated that intrusive memories were experienced more frequently by those with posttraumatic stress disorder than those with depression. Overall, the findings suggest that intrusive memories warrant clinical attention as they may contribute to the maintenance of depressive symptomatology. Copyright © 2018 John Wiley & Sons, Ltd.

IGNEOUS INTRUSION IMPACTS ON WASTE PACKAGES AND WASTE FORMS

International Nuclear Information System (INIS)

Bernot, P.

2004-01-01

The purpose of this model report is to assess the potential impacts of igneous intrusion on waste packages and waste forms in the emplacement drifts at the Yucca Mountain Repository. The models are based on conceptual models and includes an assessment of deleterious dynamic, thermal, hydrologic, and chemical impacts. The models described in this report constitute the waste package and waste form impacts submodel of the Total System Performance Assessment for the License Application (TSPA-LA) model assessing the impacts of a hypothetical igneous intrusion event on the repository total system performance. This submodel is carried out in accordance with Technical Work Plan for Waste Form Degradation Modeling, Testing, and Analyses in Support of LA (BSC 2004 [DIRS:167796]) and Total System Performance Assessment-License Application Methods and Approaches (BSC 2003 [DIRS: 166296]). The technical work plan was prepared in accordance with AP-2.27Q, Planning for Science Activities. Any deviations from the technical work plan are documented in the following sections as they occur. The TSPA-LA approach to implementing the models for waste package and waste form response during igneous intrusion is based on identification of damage zones. Zone 1 includes all emplacement drifts intruded by the basalt dike, and Zone 2 includes all other emplacement drifts in the repository that are not in Zone 1. This model report will document the following model assessments: (1) Mechanical and thermal impacts of basalt magma intrusion on the invert, waste packages and waste forms of the intersected emplacement drifts of Zone 1. (2) Temperature and pressure trends of basaltic magma intrusion intersecting Zone 1 and their potential effects on waste packages and waste forms in Zone 2 emplacement drifts. (3) Deleterious volatile gases, exsolving from the intruded basalt magma and their potential effects on waste packages of Zone 2 emplacement drifts. (4) Post-intrusive physical

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

Directory of Open Access Journals (Sweden)

Shawq Malik Mehibs

2017-12-01

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

Repeated magmatic intrusions at El Hierro Island following the 2011-2012 submarine eruption

Science.gov (United States)

Benito-Saz, Maria A.; Parks, Michelle M.; Sigmundsson, Freysteinn; Hooper, Andrew; García-Cañada, Laura

2017-09-01

After more than 200 years of quiescence, in July 2011 an intense seismic swarm was detected beneath the center of El Hierro Island (Canary Islands), culminating on 10 October 2011 in a submarine eruption, 2 km off the southern coast. Although the eruption officially ended on 5 March 2012, magmatic activity continued in the area. From June 2012 to March 2014, six earthquake swarms, indicative of magmatic intrusions, were detected underneath the island. We have studied these post-eruption intrusive events using GPS and InSAR techniques to characterize the ground surface deformation produced by each of these intrusions, and to determine the optimal source parameters (geometry, location, depth, volume change). Source inversions provide insight into the depth of the intrusions ( 11-16 km) and the volume change associated with each of them (between 0.02 and 0.13 km3). During this period, > 20 cm of uplift was detected in the central-western part of the island, corresponding to approximately 0.32-0.38 km3 of magma intruded beneath the volcano. We suggest that these intrusions result from deep magma migrating from the mantle, trapped at the mantle/lower crust discontinuity in the form of sill-like bodies. This study, using joint inversion of GPS and InSAR data in a post-eruption period, provides important insight into the characteristics of the magmatic plumbing system of El Hierro, an oceanic intraplate volcanic island.

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

Directory of Open Access Journals (Sweden)

Angelo Catalano

2014-09-01

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

Intrusion recognition for optic fiber vibration sensor based on the selective attention mechanism

Science.gov (United States)

Xu, Haiyan; Xie, Yingjuan; Li, Min; Zhang, Zhuo; Zhang, Xuewu

2017-11-01

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. A fiber optic perimeter detection system based on all-fiber interferometric sensor is proposed, through the back-end analysis, processing and intelligent identification, which can distinguish effects of different intrusion activities. In this paper, an intrusion recognition based on the auditory selective attention mechanism is proposed. Firstly, considering the time-frequency of vibration, the spectrogram is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Based on these maps, the feature matrix is formed after normalization. The system could recognize the intrusion activities occurred along the perimeter sensors. Experiment results show that the proposed method for the perimeter is able to differentiate intrusion signals from ambient noises. What's more, the recognition rate of the system is improved while deduced the false alarm rate, the approach is proved by large practical experiment and project.

Strontium isotopic geochemistry of intrusive rocks, Puerto Rico, Greater Antilles

International Nuclear Information System (INIS)

Jones, L.M.; Kesler, S.E.

1980-01-01

The strontium isotope geochemistry is given for three Puerto Rican intrusive rocks: the granodioritic Morovis and San Lorenzo plutons and the Rio Blanco stock of quartz dioritic composition. The average calculated initial 87 Sr/ 86 Sr ratios are 0.70370, 0.70355 and 0.70408, respectively. In addition, the San Lorenzo data establish a whole-rock isochron of 71 +- 2 m.y., which agrees with the previously reported K-Ar age of 73 m.y. Similarity of most of the intrusive rocks in the Greater Antilles with respect to their strontium isotopic geochemistry regardless of their major element composition indicates that intrusive magmas with a wide range of composition can be derived from a single source material. The most likely source material, in view of the available isotopic data, is the mantle wedge overlying the subduction zone. (orig.)

An international perspective on Facebook intrusion.

Science.gov (United States)

Błachnio, Agata; Przepiorka, Aneta; Benvenuti, Martina; Cannata, Davide; Ciobanu, Adela Magdalena; Senol-Durak, Emre; Durak, Mithat; Giannakos, Michail N; Mazzoni, Elvis; Pappas, Ilias O; Popa, Camelia; Seidman, Gwendolyn; Yu, Shu; Wu, Anise M S; Ben-Ezra, Menachem

2016-08-30

Facebook has become one of the most popular social networking websites in the world. The main aim of the study was to present an international comparison of Facebook intrusion and Internet penetration while examining possible gender differences. The study consisted of 2589 participants from eight countries: China, Greece, Israel, Italy, Poland, Romania, Turkey, USA. Facebook intrusion and Internet penetration were taken into consideration. In this study the relationship between Facebook intrusion and Internet penetration was demonstrated. Facebook intrusion was slightly negatively related to Internet penetration in each country. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Personalized links recommendation based on data mining in adaptive educational hypermedia systems

NARCIS (Netherlands)

Romero, C.; Ventura, S.; Delgado, J.A.; De Bra, P.M.E.; Duval, E.; Klamma, R.; Wolpers, M.

2007-01-01

In this paper, we describe a personalized recommender system that uses web mining techniques for recommending a student which (next) links to visit within an adaptable educational hypermedia system. We present a specific mining tool and a recommender engine that we have integrated in the AHA! system

Computationally Efficient Neural Network Intrusion Security Awareness

Energy Technology Data Exchange (ETDEWEB)

Todd Vollmer; Milos Manic

2009-08-01

An enhanced version of an algorithm to provide anomaly based intrusion detection alerts for cyber security state awareness is detailed. A unique aspect is the training of an error back-propagation neural network with intrusion detection rule features to provide a recognition basis. Network packet details are subsequently provided to the trained network to produce a classification. This leverages rule knowledge sets to produce classifications for anomaly based systems. Several test cases executed on ICMP protocol revealed a 60% identification rate of true positives. This rate matched the previous work, but 70% less memory was used and the run time was reduced to less than 1 second from 37 seconds.

Stochastic Tools for Network Intrusion Detection

OpenAIRE

Yu, Lu; Brooks, Richard R.

2017-01-01

With the rapid development of Internet and the sharp increase of network crime, network security has become very important and received a lot of attention. We model security issues as stochastic systems. This allows us to find weaknesses in existing security systems and propose new solutions. Exploring the vulnerabilities of existing security tools can prevent cyber-attacks from taking advantages of the system weaknesses. We propose a hybrid network security scheme including intrusion detecti...

A data-driven adaptive controller for a class of unknown nonlinear discrete-time systems with estimated PPD

Directory of Open Access Journals (Sweden)

Chidentree Treesatayapun

2015-06-01

Full Text Available An adaptive control scheme based on data-driven controller (DDC is proposed in this article. Unlike several DDC techniques, the proposed controller is constructed by an adaptive fuzzy rule emulated network (FREN which is able to include human knowledge based on controlled plant's input–output signals within the format of IF-THEN rules. Regarding to this advantage, an on-line estimation of pseudo partial derivative (PPD and resetting algorithms, which are commonly used by DDC, can be omitted here. Furthermore, a novel adaptive algorithm is introduced to minimize for both tracking error and control effort with stability analysis for the closed-loop system. The experimental system with brushed DC-motor current control is constructed to validate the performance of the proposed control scheme. Comparative results with conventional DDC and radial basis function (RBF controllers demonstrate that the proposed controller can provide the less tracking error and minimize the control effort.

Synergy of climate change and local pressures on saltwater intrusion in heterogeneous coastal aquifers

Science.gov (United States)

Abou Najm, M.; Safi, A.; El-Fadel, M.; Doummar, J.; Alameddine, I.

2016-12-01

The relative importance of climate change induced sea level rise on the salinization of a highly urbanized karstified coastal aquifers were compared with non-sustainable pumping. A 3D variable-density groundwater flow and solute transport model was used to predict the displacement of the saltwater-freshwater interface in a pilot aquifer located along the Eastern Mediterranean. The results showed that the influence of sea level rise was marginal when compared with the encroachment of salinity associated with anthropogenic abstraction. Model predictions of salinity mass and volumetric displacement of the interface corresponding to a long-term monthly transient model showed that the saltwater intrusion dynamic is highly sensitive to change in the abstraction rates which were estimated based on combinations of water consumption rates and population growth rates. Salinity encroachment, however, appeared to be more sensitive to water consumption rates in comparison to population growth rates, where a 50% increase in the rate of former led to four times more intrusion as compared to an equivalent increase in population growth rate over 20 years. Coupling both increase in population growth and increased consumption rates had a synergistic effect that aggravated the intrusion beyond the sum of the individual impacts. Adaptation strategies targeting a decrease in groundwater exploitation proved to be effective in retarding the intrusion.

The effect of destination linked feature selection in real-time network intrusion detection

CSIR Research Space (South Africa)

Mzila, P

2013-07-01

Full Text Available techniques in the network intrusion detection system (NIDS) is the feature selection technique. The ability of NIDS to accurately identify intrusion from the network traffic relies heavily on feature selection, which describes the pattern of the network...

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

Science.gov (United States)

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.

Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection

Directory of Open Access Journals (Sweden)

Kang Xie

2015-01-01

Full Text Available According to the problems of current distributed architecture intrusion detection systems (DIDS, a new online distributed intrusion detection model based on cellular neural network (CNN was proposed, in which discrete-time CNN (DTCNN was used as weak classifier in each local node and state-controlled CNN (SCCNN was used as global detection method, respectively. We further proposed a new method for design template parameters of SCCNN via solving Linear Matrix Inequality. Experimental results based on KDD CUP 99 dataset show its feasibility and effectiveness. Emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI implementation which allows the distributed intrusion detection to be performed better.

Adapting bioinformatics curricula for big data

Science.gov (United States)

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

2016-01-01

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

Workload modelling for data-intensive systems

CERN Document Server

Lassnig, Mario

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

Data Requirements for Developing Adaptations to Climate Variability and Change

International Nuclear Information System (INIS)

Basher, Reid E.

1999-01-01

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

Intrusive Images in Psychological Disorders

Science.gov (United States)

Brewin, Chris R.; Gregory, James D.; Lipton, Michelle; Burgess, Neil

2010-01-01

Involuntary images and visual memories are prominent in many types of psychopathology. Patients with posttraumatic stress disorder, other anxiety disorders, depression, eating disorders, and psychosis frequently report repeated visual intrusions corresponding to a small number of real or imaginary events, usually extremely vivid, detailed, and with highly distressing content. Both memory and imagery appear to rely on common networks involving medial prefrontal regions, posterior regions in the medial and lateral parietal cortices, the lateral temporal cortex, and the medial temporal lobe. Evidence from cognitive psychology and neuroscience implies distinct neural bases to abstract, flexible, contextualized representations (C-reps) and to inflexible, sensory-bound representations (S-reps). We revise our previous dual representation theory of posttraumatic stress disorder to place it within a neural systems model of healthy memory and imagery. The revised model is used to explain how the different types of distressing visual intrusions associated with clinical disorders arise, in terms of the need for correct interaction between the neural systems supporting S-reps and C-reps via visuospatial working memory. Finally, we discuss the treatment implications of the new model and relate it to existing forms of psychological therapy. PMID:20063969

Typed Linear Chain Conditional Random Fields and Their Application to Intrusion Detection

Science.gov (United States)

Elfers, Carsten; Horstmann, Mirko; Sohr, Karsten; Herzog, Otthein

Intrusion detection in computer networks faces the problem of a large number of both false alarms and unrecognized attacks. To improve the precision of detection, various machine learning techniques have been proposed. However, one critical issue is that the amount of reference data that contains serious intrusions is very sparse. In this paper we present an inference process with linear chain conditional random fields that aims to solve this problem by using domain knowledge about the alerts of different intrusion sensors represented in an ontology.

Engineering evaluation of intrusion prevention strategies for single-shell tanks

International Nuclear Information System (INIS)

Jenkins, C.E.

1994-01-01

In this study, previously implemented actions to prevent liquid intrusion into out-of-service single-shell tanks (SSTs), i.e., interim isolation or partial interim isolation, are investigated and expanded to identify additional cost-effective intrusion prevention techniques that could be reasonably taken until SSTs are ready for waste retrieval. Possible precipitation, groundwater, and condensation pathways and internal tank connections that could provide possible pathways for liquids are examined. Techniques to block identified potential pathways are developed and costed to determine the potential benefit to costed trade-offs for implementing the techniques. (Note: Surveillance data show increased waste surface levels for several SSTs that indicate possible liquid intrusion despite interim isolation activities.)

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

Science.gov (United States)

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Saltwater intrusion monitoring in Florida

Science.gov (United States)

Prinos, Scott T.

2016-01-01

Florida's communities are largely dependent on freshwater from groundwater aquifers. Existing saltwater in the aquifers, or seawater that intrudes parts of the aquifers that were fresh, can make the water unusable without additional processing. The quality of Florida's saltwater intrusion monitoring networks varies. In Miami-Dade and Broward Counties, for example, there is a well-designed network with recently constructed short open-interval monitoring wells that bracket the saltwater interface in the Biscayne aquifer. Geochemical analyses of water samples from the network help scientists evaluate pathways of saltwater intrusion and movement of the saltwater interface. Geophysical measurements, collected in these counties, aid the mapping of the saltwater interface and the design of monitoring networks. In comparison, deficiencies in the Collier County monitoring network include the positioning of monitoring wells, reliance on wells with long open intervals that when sampled might provide questionable results, and the inability of existing analyses to differentiate between multiple pathways of saltwater intrusion. A state-wide saltwater intrusion monitoring network is being planned; the planned network could improve saltwater intrusion monitoring by adopting the applicable strategies of the networks of Miami-Dade and Broward Counties, and by addressing deficiencies such as those described for the Collier County network.

Acknowledging the dilemmas of intrusive media

DEFF Research Database (Denmark)

Mathieu, David; Finger, Juliane; Dias, Patrcia

2017-01-01

Part of the stakeholder consultation addressed strategies that media audiences are developing to cope with pressures and intrusions in a changing media environment, characterised by digitalisation and interactive possibilities. We interviewed ten stakeholders representing interests such as content...... production, media literacy, media regulation, and activism. Consulting with these stakeholders left the impression that pressures and intrusions from media lack widespread acknowledgement, and that little is known about audiences’ strategies to cope with media. Even when intrusions are acknowledged, we find...... no consensual motivation, nor any clear avenue for action. Therefore, we have analysed different discursive positions that prevent acknowledging or taking action upon the pressures and intrusions that we presented to these stakeholders. The discursive positions are outlined below....

Investigating the Influence of Special On–Off Attacks on Challenge-Based Collaborative Intrusion Detection Networks

Directory of Open Access Journals (Sweden)

Wenjuan Li

2018-01-01

Full Text Available Intrusions are becoming more complicated with the recent development of adversarial techniques. To boost the detection accuracy of a separate intrusion detector, the collaborative intrusion detection network (CIDN has thus been developed by allowing intrusion detection system (IDS nodes to exchange data with each other. Insider attacks are a great threat for such types of collaborative networks, where an attacker has the authorized access within the network. In literature, a challenge-based trust mechanism is effective at identifying malicious nodes by sending challenges. However, such mechanisms are heavily dependent on two assumptions, which would cause CIDNs to be vulnerable to advanced insider attacks in practice. In this work, we investigate the influence of advanced on–off attacks on challenge-based CIDNs, which can respond truthfully to one IDS node but behave maliciously to another IDS node. To evaluate the attack performance, we have conducted two experiments under a simulated and a real CIDN environment. The obtained results demonstrate that our designed attack is able to compromise the robustness of challenge-based CIDNs in practice; that is, some malicious nodes can behave untruthfully without a timely detection.

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

Science.gov (United States)

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.

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

OpenAIRE

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

2011-01-01

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

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

Directory of Open Access Journals (Sweden)

V. S. Matveeva

2012-03-01

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

Uniqueness for cross-diffusion systems issuing from seawater intrusion problems

Directory of Open Access Journals (Sweden)

Catherine Choquet

2017-10-01

Full Text Available We consider a model mixing sharp and diffuse interface approaches for seawater intrusion phenomenons in confined and unconfined aquifers. More precisely, a phase field model is introduced in the boundary conditions on the virtual sharp interfaces. We thus include in the model the existence of diffuse transition zones but we preserve the simplified structure allowing front tracking. The three-dimensional problem then reduces to a two-dimensional model involving a strongly coupled system of partial differential equations of parabolic and elliptic type describing the evolution of the depth of the interface between salt- and freshwater and the evolution of the freshwater hydraulic head. Assuming a low hydraulic conductivity inside the aquifer, we prove the uniqueness of a weak solution for the model completed with initial and boundary conditions. Thanks to a generalization of a Meyer's regularity result, we establish that the gradient of the solution belongs to the space $L^r$, r>2. This additional regularity combined with the Gagliardo-Nirenberg inequality for r=4 allows to handle the nonlinearity of the system in the proof of uniqueness.

Network Intrusion Dataset Assessment

Science.gov (United States)

2013-03-01

International Conference on Computational Intelligence and Natural Computing, volume 2, pages 413–416, June 2009. • Rung Ching Chen, Kai -Fan Cheng, and...Chia-Fen Hsieh . “Using rough set and support vector machine for network intrusion detection.” International Journal of Network Security & Its...intrusion detection using FP tree rules.” Journal Of Advanced Networking and Applications, 1(1):30–39, 2009. • Ming-Yang Su, Gwo-Jong Yu , and Chun-Yuen

LIDeA: A Distributed Lightweight Intrusion Detection Architecture for Sensor Networks

DEFF Research Database (Denmark)

Giannetsos, Athanasios; Krontiris, Ioannis; Dimitriou, Tassos

2008-01-01

to achieve a more autonomic and complete defense mechanism, even against attacks that have not been anticipated in advance. In this paper, we present a lightweight intrusion detection system, called LIDeA, designed for wireless sensor networks. LIDeA is based on a distributed architecture, in which nodes......Wireless sensor networks are vulnerable to adversaries as they are frequently deployed in open and unattended environments. Preventive mechanisms can be applied to protect them from an assortment of attacks. However, more sophisticated methods, like intrusion detection systems, are needed...

Power-Aware Intrusion Detection in Mobile Ad Hoc Networks

Science.gov (United States)

Şen, Sevil; Clark, John A.; Tapiador, Juan E.

Mobile ad hoc networks (MANETs) are a highly promising new form of networking. However they are more vulnerable to attacks than wired networks. In addition, conventional intrusion detection systems (IDS) are ineffective and inefficient for highly dynamic and resource-constrained environments. Achieving an effective operational MANET requires tradeoffs to be made between functional and non-functional criteria. In this paper we show how Genetic Programming (GP) together with a Multi-Objective Evolutionary Algorithm (MOEA) can be used to synthesise intrusion detection programs that make optimal tradeoffs between security criteria and the power they consume.

A Survey on Cross-Layer Intrusion Detection System for Wireless ...

African Journals Online (AJOL)

pc

2018-03-05

Mar 5, 2018 ... forwarding, and open wireless medium are the factors that make ... Wireless Sensor Network (WSN) is a kind of network that ... These tiny sensors are mainly small sized and have low ..... they were integrated to WSN for intrusion detection in ..... Anomaly Detection Techniques for Smart City Wireless Sensor.

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

Science.gov (United States)

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

2018-02-01

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

Cross-bandwidth adaptation for ASR systems

CSIR Research Space (South Africa)

Kleynhans, N

2013-12-01

Full Text Available not be feasible for resource-scarce environments. Utilising limited amounts of in-domain data and a combination of feature normalisation and acoustic model adaptation techniques has therefore found wide use in ASR systems. Various approaches have been proposed...

Application of a Density-Dependent Numerical Model (MODHMS) to Assess Salinity Intrusion in the Biscayne Aquifer, North Miami-Dade County, Florida

Science.gov (United States)

Guha, H.; Panday, S.

2005-05-01

Miami-Dade County is located at the Southeastern part of the State of Florida adjoining the Atlantic coast. The sole drinking water source is the Biscayne Aquifer, which is an unconfined freshwater aquifer, composed of marine limestone with intermediate sand lenses. The aquifer is highly conductive with hydraulic conductivity values ranging from 1,000 ft/day to over 100,000 ft/day in some areas. Saltwater intrusion from the coast is an immediate threat to the freshwater resources of the County. Therefore, a multilayer density-dependent transient groundwater model was developed to evaluate the saltwater intrusion characteristics of the system. The model was developed using MODHMS, a finite difference, fully coupled groundwater and surface water flow and transport model. The buoyancy term is included in the equation for unconfined flow and the flow and transport equations are coupled using an iterative scheme. The transport equation was solved using an adaptive implicit total variation diminishing (TVD) scheme and anisotropy of dispersivity was included for longitudinal, transverse, vertical transverse, and vertical longitudinal directions. The model eastern boundaries extended approximately 3.5 miles into the Atlantic Ocean while the western boundary extended approximately 27 miles inland from the coast. The northern and southern boundaries extend 6 miles into Broward County and up to the C-100 canal in Miami-Dade County respectively. Close to 2 million active nodes were simulated, with horizontal discretization of 500 feet. A total of nine different statistical analyses were conducted with observed and simulated hydraulic heads. The analysis indicates that the model simulated hydraulic heads matched closely with the observed heads across the model domain. In general, the model reasonably simulated the inland extent of saltwater intrusion within the aquifer, and matched relatively well with limited observed chloride data from monitoring wells along the coast

Perceptual processing during trauma, priming and the development of intrusive memories

Science.gov (United States)

Sündermann, Oliver; Hauschildt, Marit; Ehlers, Anke

2013-01-01

Background Intrusive reexperiencing in posttraumatic stress disorder (PTSD) is commonly triggered by stimuli with perceptual similarity to those present during the trauma. Information processing theories suggest that perceptual processing during the trauma and enhanced perceptual priming contribute to the easy triggering of intrusive memories by these cues. Methods Healthy volunteers (N = 51) watched neutral and trauma picture stories on a computer screen. Neutral objects that were unrelated to the content of the stories briefly appeared in the interval between the pictures. Dissociation and data-driven processing (as indicators of perceptual processing) and state anxiety during the stories were assessed with self-report questionnaires. After filler tasks, participants completed a blurred object identification task to assess priming and a recognition memory task. Intrusive memories were assessed with telephone interviews 2 weeks and 3 months later. Results Neutral objects were more strongly primed if they occurred in the context of trauma stories than if they occurred during neutral stories, although the effect size was only moderate (ηp2=.08) and only significant when trauma stories were presented first. Regardless of story order, enhanced perceptual priming predicted intrusive memories at 2-week follow-up (N = 51), but not at 3 months (n = 40). Data-driven processing, dissociation and anxiety increases during the trauma stories also predicted intrusive memories. Enhanced perceptual priming and data-driven processing were associated with lower verbal intelligence. Limitations It is unclear to what extent these findings generalize to real-life traumatic events and whether they are specific to negative emotional events. Conclusions The results provide some support for the role of perceptual processing and perceptual priming in reexperiencing symptoms. PMID:23207970

Effect of winds and waves on salt intrusion in the Pearl River estuary

Science.gov (United States)

Gong, Wenping; Lin, Zhongyuan; Chen, Yunzhen; Chen, Zhaoyun; Zhang, Heng

2018-02-01

Salt intrusion in the Pearl River estuary (PRE) is a dynamic process that is influenced by a range of factors and to date, few studies have examined the effects of winds and waves on salt intrusion in the PRE. We investigate these effects using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system applied to the PRE. After careful validation, the model is used for a series of diagnostic simulations. It is revealed that the local wind considerably strengthens the salt intrusion by lowering the water level in the eastern part of the estuary and increasing the bottom landward flow. The remote wind increases the water mixing on the continental shelf, elevates the water level on the shelf and in the PRE and pumps saltier shelf water into the estuary by Ekman transport. Enhancement of the salt intrusion is comparable between the remote and local winds. Waves decrease the salt intrusion by increasing the water mixing. Sensitivity analysis shows that the axial down-estuary wind, is most efficient in driving increases in salt intrusion via wind straining effect.

Testing a 1-D Analytical Salt Intrusion Model and the Predictive Equation in Malaysian Estuaries

Science.gov (United States)

Gisen, Jacqueline Isabella; Savenije, Hubert H. G.

2013-04-01

Little is known about the salt intrusion behaviour in Malaysian estuaries. Study on this topic sometimes requires large amounts of data especially if a 2-D or 3-D numerical models are used for analysis. In poor data environments, 1-D analytical models are more appropriate. For this reason, a fully analytical 1-D salt intrusion model, based on the theory of Savenije in 2005, was tested in three Malaysian estuaries (Bernam, Selangor and Muar) because it is simple and requires minimal data. In order to achieve that, site surveys were conducted in these estuaries during the dry season (June-August) at spring tide by moving boat technique. Data of cross-sections, water levels and salinity were collected, and then analysed with the salt intrusion model. This paper demonstrates a good fit between the simulated and observed salinity distribution for all three estuaries. Additionally, the calibrated Van der Burgh's coefficient K, Dispersion coefficient D0, and salt intrusion length L, for the estuaries also displayed a reasonable correlations with those calculated from the predictive equations. This indicates that not only is the salt intrusion model valid for the case studies in Malaysia but also the predictive model. Furthermore, the results from this study describe the current state of the estuaries with which the Malaysian water authority in Malaysia can make decisions on limiting water abstraction or dredging. Keywords: salt intrusion, Malaysian estuaries, discharge, predictive model, dispersion

The Small Explorer Data System - A data system based on standard interfaces

Science.gov (United States)

Smith, Brian S.; Hengemihle, Jerome

1990-01-01

The Small Explorer Data System was developed by NASA Goddard Space Flight Center using a 'standard interfaces' approach. Standard interfaces make it adaptable to a wide variety of missions. The paper describes the Small Explorer Data System with particular emphasis on the standard interfaces incorporated in both the hardware and software.

Robust site security using smart seismic array technology and multi-sensor data fusion

Science.gov (United States)

Hellickson, Dean; Richards, Paul; Reynolds, Zane; Keener, Joshua

2010-04-01

Traditional site security systems are susceptible to high individual sensor nuisance alarm rates that reduce the overall system effectiveness. Visual assessment of intrusions can be intensive and manually difficult as cameras are slewed by the system to non intrusion areas or as operators respond to nuisance alarms. Very little system intrusion performance data are available other than discrete sensor alarm indications that provide no real value. This paper discusses the system architecture, integration and display of a multi-sensor data fused system for wide area surveillance, local site intrusion detection and intrusion classification. The incorporation of a novel seismic array of smart sensors using FK Beamforming processing that greatly enhances the overall system detection and classification performance of the system is discussed. Recent test data demonstrates the performance of the seismic array within several different installations and its ability to classify and track moving targets at significant standoff distances with exceptional immunity to background clutter and noise. Multi-sensor data fusion is applied across a suite of complimentary sensors eliminating almost all nuisance alarms while integrating within a geographical information system to feed a visual-fusion display of the area being secured. Real-time sensor detection and intrusion classification data is presented within a visual-fusion display providing greatly enhanced situational awareness, system performance information and real-time assessment of intrusions and situations of interest with limited security operator involvement. This approach scales from a small local perimeter to very large geographical area and can be used across multiple sites controlled at a single command and control station.

Lower crustal intrusions beneath the southern Baikal Rift Zone

DEFF Research Database (Denmark)

Nielsen, Christoffer; Thybo, Hans

2009-01-01

centre. The BEST (Baikal Explosion Seismic Transect) project acquired a 360-km long, deep seismic, refraction/wide-angle reflection profile in 2002 across southern Lake Baikal. The data from this project is used for identification of large-scale crustal structures and modelling of the seismic velocities....../s and 7.9 km/s. We interpret this feature as resulting from mafic to ultra-mafic intrusions in the form of sills. Petrological interpretation of the velocity values suggests that the intrusions are sorted by fractional crystallization into plagioclase-rich low-velocity layers and pyroxene- and olivine...

Real Time Adaptive Stream-oriented Geo-data Filtering

Directory of Open Access Journals (Sweden)

A. A. Golovkov

2016-01-01

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

Adaptive x-ray threat detection using sequential hypotheses testing with fan-beam experimental data (Conference Presentation)

Science.gov (United States)

Thamvichai, Ratchaneekorn; Huang, Liang-Chih; Ashok, Amit; Gong, Qian; Coccarelli, David; Greenberg, Joel A.; Gehm, Michael E.; Neifeld, Mark A.

2017-05-01

We employ an adaptive measurement system, based on sequential hypotheses testing (SHT) framework, for detecting material-based threats using experimental data acquired on an X-ray experimental testbed system. This testbed employs 45-degree fan-beam geometry and 15 views over a 180-degree span to generate energy sensitive X-ray projection data. Using this testbed system, we acquire multiple view projection data for 200 bags. We consider an adaptive measurement design where the X-ray projection measurements are acquired in a sequential manner and the adaptation occurs through the choice of the optimal "next" source/view system parameter. Our analysis of such an adaptive measurement design using the experimental data demonstrates a 3x-7x reduction in the probability of error relative to a static measurement design. Here the static measurement design refers to the operational system baseline that corresponds to a sequential measurement using all the available sources/views. We also show that by using adaptive measurements it is possible to reduce the number of sources/views by nearly 50% compared a system that relies on static measurements.

Adapting bioinformatics curricula for big data.

Science.gov (United States)

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. © The Author 2015. Published by Oxford University Press.

Development of safety assessment method for human intrusion scenario in Japan. Part 1. Drilling scenario database for safety assessment of geological disposal (Contract research)

International Nuclear Information System (INIS)

Nagasawa, Hirokazu; Takeda, Seiji; Kimura, Hideo; Sasaki, Toshihisa

2010-11-01

In deep geological disposal or intermediate depth disposal, human intrusion, i.e. accidental excavation or drilling into the disposal site, may make a direct or an indirect effect on the disposal system. Safety assessment method for the human intrusion scenario, that is, the evaluation code of radiological effect from the human intrusion and the data to examine the reduction of the probability of the human intrusion occurring, is essential for the future safety regulation. Assuming that drilling action into the disposal site leads to the human proximity to the radioactive waste or the damage to the barrier system (drilling scenario), we have collected both the data on borehole drilling implemented in Japan and information on actual situation of drilling activities. Based on the data and information, we provide concrete exposure scenarios associated with borehole drilling in the vicinity of the repository and model for estimating the frequency on borehole reaching the depth of repository. The frequency is characterized with the relation to objective of excavation, geographical features, and region in Japan etc. We have developed an assembly of the information mentioned above as database, including the model parameters used in the code to assess radiation dose for drilling scenario. (author)

Rate Adaptive OFDMA Communication Systems

International Nuclear Information System (INIS)

Abdelhakim, M.M.M.

2009-01-01

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

Duo: Software Defined Intrusion Tolerant System Using Dual Cluster

Directory of Open Access Journals (Sweden)

Yongjae Lee

2018-01-01

Full Text Available An intrusion tolerant system (ITS is a network security system that is composed of redundant virtual servers that are online only in a short time window, called exposure time. The servers are periodically recovered to their clean state, and any infected servers are refreshed again, so attackers have insufficient time to succeed in breaking into the servers. However, there is a conflicting interest in determining exposure time, short for security and long for performance. In other words, the short exposure time can increase security but requires more servers to run in order to process requests in a timely manner. In this paper, we propose Duo, an ITS incorporated in SDN, which can reduce exposure time without consuming computing resources. In Duo, there are two types of servers: some servers with long exposure time (White server and others with short exposure time (Gray server. Then, Duo classifies traffic into benign and suspicious with the help of SDN/NFV technology that also allows dynamically forwarding the classified traffic to White and Gray servers, respectively, based on the classification result. By reducing exposure time of a set of servers, Duo can decrease exposure time on average. We have implemented the prototype of Duo and evaluated its performance in a realistic environment.

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

Science.gov (United States)

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

2017-08-01

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

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

Science.gov (United States)

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

2011-01-07

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

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

Directory of Open Access Journals (Sweden)

Epstein Richard H

2011-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-10-15

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

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

International Nuclear Information System (INIS)

Lee, Chanyoung; Seong, Poong Hyun

2016-01-01

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

Numerical modeling of seawater intrusion in Zhoushuizi district of Dalian City, China

Science.gov (United States)

Zhao, J.; Lin, J.; Wu, J.

2013-12-01

A three-dimensional heterogeneous density-dependent numerical model was constructed to simulate the seawater intrusion process in coastal aquifers in Zhoushuizi Region, Dalian City. Model calibration was achieved through a prediction-correction method by adjusting the zonation and values of hydrogeologic parameters until the calculated heads and concentrations matched the observed values. Model validation results also showed that it was reasonable under current data conditions. Then the calibrated and validated model was applied to predict the dynamics and trend of seawater intrusion according to the current groundwater abstraction conditions in this study area 30 years after 2010. Prediction results showed that overall seawater intrusion in the future would be even more severe. Actually, with the growing of the population and development of the economy, the demand for ground water will be increasing continuously so that the problem of seawater intrusion may be more serious than that predicted by the modelin this study. Better strategies for reasonably governing exploitation of groundwater in the study area can be further developed by using this three-dimensional seawater intrusion model.

Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

KAUST Repository

Rakia, Tamer

2016-02-26

Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non- coherent hybrid FSO/RF systems, employing an adaptive combining scheme. Specifically, we activate the RF link along with the FSO link when FSO link quality is unacceptable, and adaptively set RF transmission power to ensure constant combined signal-to-noise ratio at receiver terminal. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are derived. Numerical examples show that, the hybrid FSO/RF systems with power adaptation achieve considerable outage performance improvement over conventional hybrid FSO/RF systems without power adaptation. © 2015 IEEE.

Design of uav robust autopilot based on adaptive neuro-fuzzy inference system

Directory of Open Access Journals (Sweden)

Mohand Achour Touat

2008-04-01

Full Text Available  This paper is devoted to the application of adaptive neuro-fuzzy inference systems to the robust control of the UAV longitudinal motion. The adaptive neore-fuzzy inference system model needs to be trained by input/output data. This data were obtained from the modeling of a ”crisp” robust control system. The synthesis of this system is based on the separation theorem, which defines the structure and parameters of LQG-optimal controller, and further - robust optimization of this controller, based on the genetic algorithm. Such design procedure can define the rule base and parameters of fuzzyfication and defuzzyfication algorithms of the adaptive neore-fuzzy inference system controller, which ensure the robust properties of the control system. Simulation of the closed loop control system of UAV longitudinal motion with adaptive neore-fuzzy inference system controller demonstrates high efficiency of proposed design procedure.

Conceptual Design Approach to Implementing Hardware-based Security Controls in Data Communication Systems

International Nuclear Information System (INIS)

Ibrahim, Ahmad Salah; Jung, Jaecheon

2016-01-01

In the Korean Advanced Power Reactor (APR1400), safety control systems network is electrically isolated and physically separated from non-safety systems data network. Unidirectional gateways, include data diode fiber-optic cabling and computer-based servers, transmit the plant safety critical parameters to the main control room (MCR) for control and monitoring processes. The data transmission is only one-way from safety to non-safety. Reverse communication is blocked so that safety systems network is protected from potential cyberattacks or intrusions from non-safety side. Most of commercials off-the-shelf (COTS) security devices are software-based solutions that require operating systems and processors to perform its functions. Field Programmable Gate Arrays (FPGAs) offer digital hardware solutions to implement security controls such as data packet filtering and deep data packet inspection. This paper presents a conceptual design to implement hardware-based network security controls for maintaining the availability of gateway servers. A conceptual design of hardware-based network security controls was discussed in this paper. The proposed design is aiming at utilizing the hardware-based capabilities of FPGAs together with filtering and DPI functions of COTS software-based firewalls and intrusion detection and prevention systems (IDPS). The proposed design implemented a network security perimeter between the DCN-I zone and gateway servers zone. Security control functions are to protect the gateway servers from potential DoS attacks that could affect the data availability and integrity

Conceptual Design Approach to Implementing Hardware-based Security Controls in Data Communication Systems

Energy Technology Data Exchange (ETDEWEB)

Ibrahim, Ahmad Salah; Jung, Jaecheon [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2016-10-15

In the Korean Advanced Power Reactor (APR1400), safety control systems network is electrically isolated and physically separated from non-safety systems data network. Unidirectional gateways, include data diode fiber-optic cabling and computer-based servers, transmit the plant safety critical parameters to the main control room (MCR) for control and monitoring processes. The data transmission is only one-way from safety to non-safety. Reverse communication is blocked so that safety systems network is protected from potential cyberattacks or intrusions from non-safety side. Most of commercials off-the-shelf (COTS) security devices are software-based solutions that require operating systems and processors to perform its functions. Field Programmable Gate Arrays (FPGAs) offer digital hardware solutions to implement security controls such as data packet filtering and deep data packet inspection. This paper presents a conceptual design to implement hardware-based network security controls for maintaining the availability of gateway servers. A conceptual design of hardware-based network security controls was discussed in this paper. The proposed design is aiming at utilizing the hardware-based capabilities of FPGAs together with filtering and DPI functions of COTS software-based firewalls and intrusion detection and prevention systems (IDPS). The proposed design implemented a network security perimeter between the DCN-I zone and gateway servers zone. Security control functions are to protect the gateway servers from potential DoS attacks that could affect the data availability and integrity.

Adaptivity in Professional Printing Systems

NARCIS (Netherlands)

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

2013-01-01

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

Effect of winds and waves on salt intrusion in the Pearl River estuary

Directory of Open Access Journals (Sweden)

W. Gong

2018-02-01

Full Text Available Salt intrusion in the Pearl River estuary (PRE is a dynamic process that is influenced by a range of factors and to date, few studies have examined the effects of winds and waves on salt intrusion in the PRE. We investigate these effects using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST modeling system applied to the PRE. After careful validation, the model is used for a series of diagnostic simulations. It is revealed that the local wind considerably strengthens the salt intrusion by lowering the water level in the eastern part of the estuary and increasing the bottom landward flow. The remote wind increases the water mixing on the continental shelf, elevates the water level on the shelf and in the PRE and pumps saltier shelf water into the estuary by Ekman transport. Enhancement of the salt intrusion is comparable between the remote and local winds. Waves decrease the salt intrusion by increasing the water mixing. Sensitivity analysis shows that the axial down-estuary wind, is most efficient in driving increases in salt intrusion via wind straining effect.

Effective use of surface-water management to control saltwater intrusion

Science.gov (United States)

Hughes, J. D.; White, J.

2012-12-01

The Biscayne aquifer in southeast Florida is susceptible to saltwater intrusion and inundation from rising sea-level as a result of high groundwater withdrawal rates and low topographic relief. Groundwater levels in the Biscayne aquifer are managed by an extensive canal system that is designed to control flooding, supply recharge to municipal well fields, and control saltwater intrusion. We present results from an integrated surface-water/groundwater model of a portion of the Biscayne aquifer to evaluate the ability of the existing managed surface-water control network to control saltwater intrusion. Surface-water stage and flow are simulated using a hydrodynamic model that solves the diffusive-wave approximation of the depth-integrated shallow surface-water equations. Variable-density groundwater flow and fluid density are solved using the Oberbeck--Boussinesq approximation of the three-dimensional variable-density groundwater flow equation and a sharp interface approximation, respectively. The surface-water and variable-density groundwater domains are implicitly coupled during each Picard iteration. The Biscayne aquifer is discretized into a multi-layer model having a 500-m square horizontal grid spacing. All primary and secondary surface-water features in the active model domain are discretized into segments using the 500-m square horizontal grid. A 15-year period of time is simulated and the model includes 66 operable surface-water control structures, 127 municipal production wells, and spatially-distributed daily internal and external hydrologic stresses. Numerical results indicate that the existing surface-water system can be effectively used in many locations to control saltwater intrusion in the Biscayne aquifer resulting from increases in groundwater withdrawals or sea-level rise expected to occur over the next 25 years. In other locations, numerical results indicate surface-water control structures and/or operations may need to be modified to control

Turbine system and adapter

Science.gov (United States)

Hogberg, Nicholas Alvin; Garcia-Crespo, Andres Jose

2017-05-30

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

Rapid laccolith intrusion driven by explosive volcanic eruption.

Science.gov (United States)

Castro, Jonathan M; Cordonnier, Benoit; Schipper, C Ian; Tuffen, Hugh; Baumann, Tobias S; Feisel, Yves

2016-11-23

Magmatic intrusions and volcanic eruptions are intimately related phenomena. Shallow magma intrusion builds subsurface reservoirs that are drained by volcanic eruptions. Thus, the long-held view is that intrusions must precede and feed eruptions. Here we show that explosive eruptions can also cause magma intrusion. We provide an account of a rapidly emplaced laccolith during the 2011 rhyolite eruption of Cordón Caulle, Chile. Remote sensing indicates that an intrusion began after eruption onset and caused severe (>200 m) uplift over 1 month. Digital terrain models resolve a laccolith-shaped body ∼0.8 km 3 . Deformation and conduit flow models indicate laccolith depths of only ∼20-200 m and overpressures (∼1-10 MPa) that likely stemmed from conduit blockage. Our results show that explosive eruptions may rapidly force significant quantities of magma in the crust to build laccoliths. These iconic intrusions can thus be interpreted as eruptive features that pose unique and previously unrecognized volcanic hazards.

Free to love? The role of intrusive parenting for young adult children's romantic relationship quality.

Science.gov (United States)

Parise, Miriam; Manzi, Claudia; Donato, Silvia; Iafrate, Raffaella

2017-01-01

Intrusive parenting is a form of boundary disturbance in the parent-child relationship which has been consistently associated with children's maladjustment. The present study examines the role of intrusive parenting for young adult children's romantic relationship quality. Relying on data from a two-wave longitudinal study among young couples in transition to marriage in Italy, we investigated the link between young adults' perceived intrusive parenting and change in their romantic relationship quality from 6 months before marriage to 18 months after marriage, as well as the mediating role of change in the capacity to include the partner in the self. Data were analyzed using actor-partner interdependence modeling. Perceived intrusive parenting negatively predicted change in inclusion of the other in the self and change in romantic relationship quality for both partners. For females, change in their capacity of inclusion of the other in the self fully mediated the association between their perceived intrusive parenting and change in their own and partner's relationship quality. Limitations and implications for practice are discussed.

Pattern Discovery in Time-Ordered Data; TOPICAL

International Nuclear Information System (INIS)

CONRAD, GREGORY N.; BRITANIK, JOHN M.; DELAND, SHARON M.; JENKIN, CHRISTINA L.

2002-01-01

This report describes the results of a Laboratory-Directed Research and Development project on techniques for pattern discovery in discrete event time series data. In this project, we explored two different aspects of the pattern matching/discovery problem. The first aspect studied was the use of Dynamic Time Warping for pattern matching in continuous data. In essence, DTW is a technique for aligning time series along the time axis to optimize the similarity measure. The second aspect studied was techniques for discovering patterns in discrete event data. We developed a pattern discovery tool based on adaptations of the A-priori and GSP (Generalized Sequential Pattern mining) algorithms. We then used the tool on three different application areas-unattended monitoring system data from a storage magazine, computer network intrusion detection, and analysis of robot training data

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

Science.gov (United States)

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

2014-11-01

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

Intrusive and Non-Intrusive Load Monitoring (A Survey

Directory of Open Access Journals (Sweden)

Marco Danilo Burbano Acuña

2015-05-01

Full Text Available There is not discussion about the need of energyconservation, it is well known that energy resources are limitedmoreover the global energy demands will double by the end of2030, which certainly will bring implications on theenvironment and hence to all of us.Non-Intrusive load monitoring (NILM is the process ofrecognize electrical devices and its energy consumption basedon whole home electric signals, where this aggregated load datais acquired from a single point of measurement outside thehousehold. The aim of this approach is to get optimal energyconsumption and avoid energy wastage. Intrusive loadmonitoring (ILM is the process of identify and locate singledevices through the use of sensing systems to support control,monitor and intervention of such devices. The aim of thisapproach is to offer a base for the development of importantapplications for remote and automatic intervention of energyconsumption inside buildings and homes as well. For generalpurposes this paper states a general framework of NILM andILM approaches.Appliance discerns can be tackled using approaches fromdata mining and machine learning, finding out the techniquesthat fit the best this requirements, is a key factor for achievingfeasible and suitable appliance load monitoring solutions. Thispaper presents common and interesting methods used.Privacy concerns have been one of the bigger obstacles forimplementing a widespread adoption of these solutions; despitethis fact, developed countries like those inside the EU and theUK have established a deadline for the implementation ofsmart meters in the whole country, whereas USA governmentstill struggles with the acceptance of this solution by itscitizens.The implementation of security over these approachesalong with fine-grained energy monitoring would lead to abetter public agreement of these solutions and hence a fasteradoption of such approaches. This paper reveals a lack ofsecurity over these approaches with a real scenario.

Generic adaptation framework for unifying adaptive web-based systems

NARCIS (Netherlands)

Knutov, E.

2012-01-01

The Generic Adaptation Framework (GAF) research project first and foremost creates a common formal framework for describing current and future adaptive hypermedia (AHS) and adaptive webbased systems in general. It provides a commonly agreed upon taxonomy and a reference model that encompasses the

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

Science.gov (United States)

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

2015-01-01

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

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

International Nuclear Information System (INIS)

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

2009-01-01

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

Fracturing of doleritic intrusions and associated contact zones: Implications for fluid flow in volcanic basins

Science.gov (United States)

Senger, Kim; Buckley, Simon J.; Chevallier, Luc; Fagereng, Åke; Galland, Olivier; Kurz, Tobias H.; Ogata, Kei; Planke, Sverre; Tveranger, Jan

2015-02-01

Igneous intrusions act as both carriers and barriers to subsurface fluid flow and are therefore expected to significantly influence the distribution and migration of groundwater and hydrocarbons in volcanic basins. Given the low matrix permeability of igneous rocks, the effective permeability in- and around intrusions is intimately linked to the characteristics of their associated fracture networks. Natural fracturing is caused by numerous processes including magma cooling, thermal contraction, magma emplacement and mechanical disturbance of the host rock. Fracturing may be locally enhanced along intrusion-host rock interfaces, at dyke-sill junctions, or at the base of curving sills, thereby potentially enhancing permeability associated with these features. In order to improve our understanding of fractures associated with intrusive bodies emplaced in sedimentary host rocks, we have investigated a series of outcrops from the Karoo Basin of the Eastern Cape province of South Africa, where the siliciclastic Burgersdorp Formation has been intruded by various intrusions (thin dykes, mid-sized sheet intrusions and thick sills) belonging to the Karoo dolerite. We present a quantified analysis of fracturing in- and around these igneous intrusions based on five outcrops at three individual study sites, utilizing a combination of field data, high-resolution lidar virtual outcrop models and image processing. Our results show a significant difference between the three sites in terms of fracture orientation. The observed differences can be attributed to contrasting intrusion geometries, outcrop geometry (for lidar data) and tectonic setting. Two main fracture sets were identified in the dolerite at two of the sites, oriented parallel and perpendicular to the contact respectively. Fracture spacing was consistent between the three sites, and exhibits a higher degree of variation in the dolerites compared to the host rock. At one of the study sites, fracture frequency in the

Analogue modelling on the interaction between shallow magma intrusion and a strike-slip fault: Application on the Middle Triassic Monzoni Intrusive Complex (Dolomites, Italy)

Science.gov (United States)

Michail, Maria; Coltorti, Massimo; Gianolla, Piero; Riva, Alberto; Rosenau, Matthias; Bonadiman, Costanza; Galland, Olivier; Guldstrand, Frank; Thordén Haug, Øystein; Rudolf, Michael; Schmiedel, Tobias

2017-04-01

The southwestern part of the Dolomites in Northern Italy has undergone a short-lived Ladinian (Middle Triassic) tectono-magmatic event, forming a series of significant magmatic features. These intrusive bodies deformed and metamorphosed the Permo-Triassic carbonate sedimentary framework. In this study we focus on the tectono-magmatic evolution of the shallow shoshonitic Monzoni Intrusive Complex of this Ladinian event (ca 237 Ma), covering an area of 20 km^2. This NW-SE elongated intrusive structure (5 km length) shows an orogenic magmatic affinity which is in contrast to the tectonic regime at the time of intrusion. Strain analysis shows anorogenic transtensional displacement in accordance with the ENE-WSW extensional pattern in the central Dolomites during the Ladinian. Field interpretations led to a detailed description of the regional stratigraphic sequence and the structural features of the study area. However, the geodynamic context of this magmatism and the influence of the inherited strike-slip fault on the intrusion, are still in question. To better understand the specific natural prototype and the general mechanisms of magma emplacement in tectonically active areas, we performed analogue experiments defined by, but not limited to, first order field observations. We have conducted a systematic series of experiments in different tectonic regimes (static conditions, strike-slip, transtension). We varied the ratio of viscous to brittle stresses between magma and country rock, by injecting Newtonian fluids both of high and low viscosity (i.e. silicone oil/vegetable oil) into granular materials of varying cohesion (sand, silica flour, glass beads). The evolving surface and side view of the experiments were monitored by photogrammetric techniques for strain analyses and topographic evolution. In our case, the combination of the results from field and analogue experiments brings new insights regarding the tectonic regime, the geometry of the intrusive body, and

Complex Adaptive Systems of Systems (CASOS) engineering environment.

Energy Technology Data Exchange (ETDEWEB)

Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

2012-02-01

Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

Young women's experiences of intrusive behavior in 12 countries.

Science.gov (United States)

Sheridan, Lorraine; Scott, Adrian J; Roberts, Karl

2016-01-01

The present study provides international comparisons of young women's (N = 1,734) self-reported experiences of intrusive activities enacted by men. Undergraduate psychology students from 12 countries (Armenia, Australia, England, Egypt, Finland, India, Indonesia, Italy, Japan, Portugal, Scotland, and Trinidad) indicated which of 47 intrusive activities they had personally experienced. Intrusive behavior was not uncommon overall, although large differences were apparent between countries when women's personal experiences of specific intrusive activities were compared. Correlations were carried out between self-reported intrusive experiences, the Gender Empowerment Measure (GEM), and Hofstede's dimensions of national cultures. The primary associations were between women's experiences of intrusive behavior and the level of power they are afforded within the 12 countries. Women from countries with higher GEM scores reported experiencing more intrusive activities relating to courtship and requests for sex, while the experiences of women from countries with lower GEM scores related more to monitoring and ownership. Intrusive activities, many of them constituent of harassment and stalking, would appear to be widespread and universal, and their incidence and particular form reflect national level gender inequalities. © 2015 Wiley Periodicals, Inc.

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

Science.gov (United States)

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.

Potential for saltwater intrusion into the lower Tamiami aquifer near Bonita Springs, southwestern Florida

Science.gov (United States)

Shoemaker, W. Barclay; Edwards, K. Michelle

2003-01-01

A study was conducted to examine the potential for saltwater intrusion into the lower Tamiami aquifer beneath Bonita Springs in southwestern Florida. Field data were collected, and constant- and variable-density ground-water flow simulations were performed that: (1) spatially quantified modern and seasonal stresses, (2) identified potential mechanisms of saltwater intrusion, and (3) estimated the potential extent of saltwater intrusion for the area of concern. MODFLOW and the inverse modeling routine UCODE were used to spatially quantify modern and seasonal stresses by calibrating a constant-density ground-water flow model to field data collected in 1996. The model was calibrated by assuming hydraulic conductivity parameters were accurate and by estimating unmonitored ground-water pumpage and potential evapotranspiration with UCODE. Uncertainty in these estimated parameters was quantified with 95-percent confidence intervals. These confidence intervals indicate more uncertainty (or less reliability) in the estimates of unmonitored ground-water pumpage than estimates of pan-evaporation multipliers, because of the nature and distribution of observations used during calibration. Comparison of simulated water levels, streamflows, and net recharge with field data suggests the model is a good representation of field conditions. Potential mechanisms of saltwater intrusion into the lower Tamiami aquifer include: (1) lateral inland movement of the freshwater-saltwater interface from the southwestern coast of Florida; (2) upward leakage from deeper saline water-bearing zones through natural upwelling and upconing, both of which could occur as diffuse upward flow through semiconfining layers, conduit flow through karst features, or pipe flow through leaky artesian wells; (3) downward leakage of saltwater from surface-water channels; and (4) movement of unflushed pockets of relict seawater. Of the many potential mechanisms of saltwater intrusion, field data and variable

Enhancing collaborative intrusion detection networks against insider attacks using supervised intrusion sensitivity-based trust management model

DEFF Research Database (Denmark)

Li, Wenjuan; Meng, Weizhi; Kwok, Lam-For

2017-01-01

To defend against complex attacks, collaborative intrusion detection networks (CIDNs) have been developed to enhance the detection accuracy, which enable an IDS to collect information and learn experience from others. However, this kind of networks is vulnerable to malicious nodes which are utili......To defend against complex attacks, collaborative intrusion detection networks (CIDNs) have been developed to enhance the detection accuracy, which enable an IDS to collect information and learn experience from others. However, this kind of networks is vulnerable to malicious nodes which...... are utilized by insider attacks (e.g., betrayal attacks). In our previous research, we developed a notion of intrusion sensitivity and identified that it can help improve the detection of insider attacks, whereas it is still a challenge for these nodes to automatically assign the values. In this article, we...... of intrusion sensitivity based on expert knowledge. In the evaluation, we compare the performance of three different supervised classifiers in assigning sensitivity values and investigate our trust model under different attack scenarios and in a real wireless sensor network. Experimental results indicate...

Single-process versus multiple-strategy models of decision making: evidence from an information intrusion paradigm.

Science.gov (United States)

Söllner, Anke; Bröder, Arndt; Glöckner, Andreas; Betsch, Tilmann

2014-02-01

When decision makers are confronted with different problems and situations, do they use a uniform mechanism as assumed by single-process models (SPMs) or do they choose adaptively from a set of available decision strategies as multiple-strategy models (MSMs) imply? Both frameworks of decision making have gathered a lot of support, but only rarely have they been contrasted with each other. Employing an information intrusion paradigm for multi-attribute decisions from givens, SPM and MSM predictions on information search, decision outcomes, attention, and confidence judgments were derived and tested against each other in two experiments. The results consistently support the SPM view: Participants seemingly using a "take-the-best" (TTB) strategy do not ignore TTB-irrelevant information as MSMs would predict, but adapt the amount of information searched, choose alternative choice options, and show varying confidence judgments contingent on the quality of the "irrelevant" information. The uniformity of these findings underlines the adequacy of the novel information intrusion paradigm and comprehensively promotes the notion of a uniform decision making mechanism as assumed by single-process models. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Model-based design of adaptive embedded systems

CERN Document Server

Hamberg, Roelof; Reckers, Frans; Verriet, Jacques

2013-01-01

Today’s embedded systems have to operate in a wide variety of dynamically changing environmental circumstances. Adaptivity, the ability of a system to autonomously adapt itself, is a means to optimise a system’s behaviour to accommodate changes in its environment. It involves making in-product trade-offs between system qualities at system level. The main challenge in the development of adaptive systems is keeping control of the intrinsic complexity of such systems while working with multi-disciplinary teams to create different parts of the system. Model-Based Development of Adaptive Embedded Systems focuses on the development of adaptive embedded systems both from an architectural and methodological point of view. It describes architectural solution patterns for adaptive systems and state-of-the-art model-based methods and techniques to support adaptive system development. In particular, the book describes the outcome of the Octopus project, a cooperation of a multi-disciplinary team of academic and indus...

USING THE ADAPTED DLP SYSTEM FOR BLOCKING INFORMATION LEAKS

Directory of Open Access Journals (Sweden)

T. A. Andryianava

2017-01-01

Full Text Available The importance of using the adapted DLP-system in the «Blocking» mode of leaking confidential information of the company is investigated. The scheme of interception of information security events in the «Copy» mode is given, the analysis of which reflects the main drawback of using this mode – the DLP-system works only with copies of confidential documents, while the originals were delivered to the recipient. Such cases inflict enormous damage on companies, so the transfer of critical information beyond the corporate network is unacceptable.A solution is proposed for transferring the operation of the DLP-system from the «Copy» mode to the «Blocking» mode. It is important that the operation of the DLP-system does not hinder the staff members from performing regular operations and does not hinder business processes. Therefore, it is mandatory to adapt the standard DLP-system to the specifics of the company’s activities. After that the transition of the adapted DLP-system to the «Blocking» mode is carried out.Developed: the transition procedure of the adapted DLP-system from the «Copy» mode to the «Blocking» mode, the scheme of the event capture by the DLP-system for the two modes. The main channels of data leaks were investigated, the main leaks were identified by the data type and by the transmission channel. The analysis of the DLP-system operation in the «Blocking» mode is performed.

Systematic, Multimethod Assessment of Adaptations Across Four Diverse Health Systems Interventions

Directory of Open Access Journals (Sweden)

Borsika A. Rabin

2018-04-01

Full Text Available BackgroundMany health outcomes and implementation science studies have demonstrated the importance of tailoring evidence-based care interventions to local context to improve fit. By adapting to local culture, history, resources, characteristics, and priorities, interventions are more likely to lead to improved outcomes. However, it is unclear how best to adapt evidence-based programs and promising innovations. There are few guides or examples of how to best categorize or assess health-care adaptations, and even fewer that are brief and practical for use by non-researchers.Materials and methodsThis study describes the importance and potential of assessing adaptations before, during, and after the implementation of health systems interventions. We present a promising multilevel and multimethod approach developed and being applied across four different health systems interventions. Finally, we discuss implications and opportunities for future research.ResultsThe four case studies are diverse in the conditions addressed, interventions, and implementation strategies. They include two nurse coordinator-based transition of care interventions, a data and training-driven multimodal pain management project, and a cardiovascular patient-reported outcomes project, all of which are using audit and feedback. We used the same modified adaptation framework to document changes made to the interventions and implementation strategies. To create the modified framework, we started with the adaptation and modification model developed by Stirman and colleagues and expanded it by adding concepts from the RE-AIM framework. Our assessments address the intuitive domains of Who, How, When, What, and Why to classify and organize adaptations. For each case study, we discuss how the modified framework was operationalized, the multiple methods used to collect data, results to date and approaches utilized for data analysis. These methods include a real-time tracking system and

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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.

Inverse modeling for seawater intrusion in coastal aquifers: Insights about parameter sensitivities, variances, correlations and estimation procedures derived from the Henry problem

Science.gov (United States)

Sanz, E.; Voss, C.I.

2006-01-01

Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only

Model-Free Adaptive Control Algorithm with Data Dropout Compensation

Directory of Open Access Journals (Sweden)

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.

Intrusion detection in Mobile Ad-hoc Networks: Bayesian game formulation

Directory of Open Access Journals (Sweden)

Basant Subba

2016-06-01

Full Text Available Present Intrusion Detection Systems (IDSs for MANETs require continuous monitoring which leads to rapid depletion of a node's battery life. To address this issue, we propose a new IDS scheme comprising a novel cluster leader election process and a hybrid IDS. The cluster leader election process uses the Vickrey–Clarke–Groves mechanism to elect the cluster leader which provides the intrusion detection service. The hybrid IDS comprises a threshold based lightweight module and a powerful anomaly based heavyweight module. Initially, only the lightweight module is activated. The decision to activate the heavyweight module is taken by modeling the intrusion detection process as an incomplete information non-cooperative game between the elected leader node and the potential malicious node. Simulation results show that the proposed scheme significantly reduces the IDS traffic and overall power consumption in addition to maintaining a high detection rate and accuracy.

Adaptive Modeling of the International Space Station Electrical Power System

Science.gov (United States)

Thomas, Justin Ray

2007-01-01

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

The Sonju Lake layered intrusion, northeast Minnesota: Internal structure and emplacement history inferred from magnetic fabrics

Science.gov (United States)

Maes, S.M.; Tikoff, B.; Ferre, E.C.; Brown, P.E.; Miller, J.D.

2007-01-01

The Sonju Lake intrusion (SLI), in northeastern Minnesota, is a layered mafic complex of Keweenawan age (1096.1 ?? 0.8 Ma) related to the Midcontinent rift. The cumulate paragenesis of the intrusion is recognized as broadly similar to the Skaergaard intrusion, a classic example of closed-system differentiation of a tholeiitic mafic magma. The SLI represents nearly closed-system differentiation through bottom-up fractional crystallization. Geochemical studies have identified the presence of a stratabound, 50-100 m thick zone anomalously enriched in Au + PGE. Similar to the PGE reefs of the Skaergaard intrusion, this PGE-enriched zone is hosted within oxide gabbro cumulates, about two-third of the way up from the base of the intrusion. We present a petrofabric study using the anisotropy of magnetic susceptibility (AMS) to investigate the emplacement and flow patterns within the Sonju Lake intrusion. Petrographic and electron microprobe studies, combined with AMS and hysteresis measurements indicate the primary source of the magnetic signal is pseudo-single domain (PSD) magnetite or titanomagnetite. Low field AMS was measured at 32 sites within the Sonju Lake intrusion, which provided information about primary igneous fabrics. The magnetic fabrics in the layered series of the Sonju Lake intrusion are consistent with sub-horizontal to inclined emplacement of the intrusion and show evidence that the cumulate layers were deposited in a dynamic environment. Well-aligned magnetic lineations, consistently plunging shallowly toward the southwest, indicate the source of the magma is a vertical sill-like feeder, presumably located beneath the Finland granite. The Finland granite acted as a density trap for the Sonju Lake magmas, forcing lateral flow of magma to the northeast. The strongly oblate magnetic shape fabrics indicate the shallowly dipping planar fabrics were enhanced by compaction of the crystal mush. ?? 2007 Elsevier B.V. All rights reserved.

A fuzzy multicriteria categorization of the GALDIT method to assess seawater intrusion vulnerability of coastal aquifers.

Science.gov (United States)

Kazakis, Nerantzis; Spiliotis, Mike; Voudouris, Konstantinos; Pliakas, Fotios-Konstantinos; Papadopoulos, Basil

2018-04-15

Groundwater constitutes the primary source of fresh water for >1.2 billion people living in coastal zones. However, the threat of seawater intrusion is widespread in coastal aquifers mainly due to overexploitation of groundwater. In the present study, a modified fuzzy multicriteria categorization into non-ordered categories method was developed in order to modify the standard GALDIT method and assess seawater intrusion vulnerability in a coastal aquifer of northern Greece. The method is based on six parameters: groundwater occurrence, aquifer hydraulic conductivity, groundwater level, distance from the shore, impact of the existing status of seawater intrusion, and aquifer thickness. Initially, the original method was applied and revealed a zone of high vulnerability running parallel to the coastline and covering an area of 8.6km 2 . The modified GALDIT-F method achieved higher discretization of vulnerability zones which is essential to build a rational management plan to prevent seawater intrusion. The GALDIT-F approach also distinguished an area of the aquifer that is influenced by geothermal fluids. In total, twenty-five categories were produced corresponding to different vulnerability degrees according to the initial method (High, Moderate, Low) as well as the area influenced by geothermal fluids. Finally, a road map was developed in order to adapt management strategies to GALDIT-F categories and prevent and mitigate seawater intrusion. The proposed management strategies of the coastal aquifer include managed aquifer recharge (MAR) implementation, reallocation of existing wells, optimization of pumping rates during the hydrological year, and a detailed monitoring plan. Copyright © 2017 Elsevier B.V. All rights reserved.

Stress, intrusive imagery, and chronic distress

International Nuclear Information System (INIS)

Baum, A.

1990-01-01

Discusses the nature of stress in the context of problems with its definition and sources of confusion regarding its usefulness and specificity. Stress can be defined as a negative emotional experience accompanied by predictable biochemical, physiological, and behavioral changes that are directed toward adaptation either by manipulating the situation to alter the stressor or by accommodating its effects. Chronic stress is more complex than most definitions suggest and is clearly not limited to situations in which stressors persist for long periods of time. Responses may habituate before a stressor disappears or may persist long beyond the physical presence of the stressor. This latter case, in which chronic stress and associated biobehavioral changes outlast their original cause, is considered in light of research at Three Mile Island and among Vietnam veterans. The role of intrusive images of the stressor or uncontrollable thoughts about it in maintaining stress is explored

Intrusive Memories of Distressing Information: An fMRI Study.

Directory of Open Access Journals (Sweden)

Eva Battaglini

Full Text Available Although intrusive memories are characteristic of many psychological disorders, the neurobiological underpinning of these involuntary recollections are largely unknown. In this study we used functional magentic resonance imaging (fMRI to identify the neural networks associated with encoding of negative stimuli that are subsequently experienced as intrusive memories. Healthy partipants (N = 42 viewed negative and neutral images during a visual/verbal processing task in an fMRI context. Two days later they were assessed on the Impact of Event Scale for occurrence of intrusive memories of the encoded images. A sub-group of participants who reported significant intrusions (n = 13 demonstrated stronger activation in the amygdala, bilateral ACC and parahippocampal gyrus during verbal encoding relative to a group who reported no intrusions (n = 13. Within-group analyses also revealed that the high intrusion group showed greater activity in the dorsomedial (dmPFC and dorsolateral prefrontal cortex (dlPFC, inferior frontal gyrus and occipital regions during negative verbal processing compared to neutral verbal processing. These results do not accord with models of intrusions that emphasise visual processing of information at encoding but are consistent with models that highlight the role of inhibitory and suppression processes in the formation of subsequent intrusive memories.

Problems of Aero-optics and Adaptive Optical Systems: Analytical Review

Directory of Open Access Journals (Sweden)

Yu. I. Shanin

2017-01-01

Full Text Available The analytical review gives the basic concepts of the aero-optics problem arising from the radiation propagation in the region of the boundary layers of a laser installation carrier aircraft. Estimates the radiation wave front distortions at its propagation in the near and far field. Presents main calculation approaches and methods to solve the gas-dynamic and optical problems in propagating laser radiation. Conducts a detailed analysis of the flows and their generating optical aberrations introduced by the aircraft turret (a projection platform of the on-board laser. Considers the effect of various factors (shock wave, difference in wall and flow temperatures on the flow pattern and the optical aberrations. Provides research data on the aero-optics obtained in the flying laboratory directly while in flight. Briefly considers the experimental research methods, diagnostic equipment, and synthesis of results while studying the aero-optics problem. Discusses some methods for mitigating the aerodynamic effects on the light propagation under flight conditions. Presents data about the passive, active, and hybrid effects on the flow in the boundary layers in order to reduce aberrations through improving the flow aerodynamics.The paper considers operation of adaptive optical systems under conditions of aero-optical distortions. Presents the study results concerning the reduction of the aero-optics effect on the characteristics of radiation in far field. Gives some research results regarding the effect on the efficiency of the adaptive system of a laser beam jitter and a time delay in the feedback signal transmission, which occur under application conditions. Provides data on adaptive correction of aero-optical wave fronts of radiation. Considers some application aspects in control systems of the on-board adaptive optics of adaptive filtration as a way to improve the efficiency of adaptive optical systems. The project in mind is to use obtained results

Biological intrusion of low-level-waste trench covers

International Nuclear Information System (INIS)

Hakonson, T.E.; Gladney, E.S.

1981-01-01

The long-term integrity of low-level waste shallow land burial sites is dependent on the interaction of physical, chemical, and biological factors that modify the waste containment system. Past research on low-level waste shallow land burial methods has emphasized physical (i.e., water infiltration, soil erosion) and chemical (radionuclide leaching) processes that can cause waste site failure and subsequent radionuclide transport. The purpose of this paper is to demonstrate the need to consider biological processes as being potentially important in reducing the integrity of waste burial site cover treatments. Plants and animals not only can transport radionuclides to the ground surface via root systems and soil excavated from the cover profile by animal burrowing activities, but they modify physical and chemical processes within the cover profile by changing the water infiltration rates, soil erosion rates and chemical composition of the soil. One approach to limiting biological intrusion through the waste cover is to apply a barrier within the profile to limit root and animal penetration with depth. Experiments in the Los Alamos Experimental Engineered Test Facility were initiated to develop and evaluate biological barriers that are effective in minimizing intrusion into waste trenches. The experiments that are described employ four different candidate barrier materials of geologic origin. Experimental variables that will be evaluated, in addition to barrier type, are barrier depth and soil overburden depth. The rate of biological intrusion through the various barrier materials is being evaluated through the use of activatable stable tracers

Full distributed fiber optical sensor for intrusion detection in application to buried pipelines

Science.gov (United States)

Gao, Jianzhong; Jiang, Zhuangde; Zhao, Yulong; Zhu, Li; Zhao, Guoxian

2005-11-01

Based on the microbend effect of optical fiber, a distributed sensor for real-time continuous monitoring of intrusion in application to buried pipelines is proposed. The sensing element is a long cable with a special structure made up of an elastic polymer wire, an optical fiber, and a metal wire. The damage point is located with an embedded optical time domain reflectometry (OTDR) instrument. The intrusion types can be indicated by the amplitude of output voltage. Experimental results show that the detection system can alarm adequately under abnormal load and can locate the intrusion point within 22.4 m for distance of 3.023 km.

Semantic models for adaptive interactive systems

CERN Document Server

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

2013-01-01

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

Computerized adaptive testing item selection in computerized adaptive learning systems

NARCIS (Netherlands)

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

2012-01-01

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

Magmatic sill intrusions beneath El Hierro Island following the 2011-2012 submarine eruption

Science.gov (United States)

Benito-Saz, María Á.; Sigmundsson, Freysteinn; Parks, Michelle M.; García-Cañada, Laura; Domínguez Cerdeña, Itahiza

2016-04-01

El Hierro, the most southwestern island of Canary Islands, Spain, is a volcano rising from around 3600 m above the ocean floor and up to of 1500 m above sea level. A submarine eruption occurred off the coast of El Hierro in 2011-2012, which was the only confirmed eruption in the last ~ 600 years. Activity continued after the end of the eruption with six magmatic intrusions occurring between 2012-2014. Each of these intrusions was characterized by hundreds of earthquakes and 3-19 centimeters of observed ground deformation. Ground displacements at ten continuous GPS sites were initially inverted to determine the optimal source parameters (location, geometry, volume/pressure change) that best define these intrusions from a geodetic point of view. Each intrusive period appears to be associated with the formation of a separate sill, with inferred volumes between 0.02 - 0.3 km3. SAR images from the Canadian RADARSAT-2 satellite and the Italian Space Agency COSMO-SkyMed constellation have been used to produce high-resolution detailed maps of line-of-sight displacements for each of these intrusions. These data have been combined with the continuous GPS observations and a joint inversion undertaken to gain further constraints on the optimal source parameters for each of these separate intrusive events. The recorded activity helps to understand how an oceanic intraplate volcanic island grows through repeated sill intrusions; well documented by seismic, GPS and InSAR observations in the case of the El Hierro activity.

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

Science.gov (United States)

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

Security engineering: systems engineering of security through the adaptation and application of risk management

Science.gov (United States)

Gilliam, David P.; Feather, Martin S.

2004-01-01

Information Technology (IT) Security Risk Management is a critical task in the organization, which must protect its resources and data against the loss of confidentiality, integrity, and availability. As systems become more complex and diverse, and more vulnerabilities are discovered while attacks from intrusions and malicious content increase, it is becoming increasingly difficult to manage IT security. This paper describes an approach to address IT security risk through risk management and mitigation in both the institution and in the project life cycle.

Front-end data processing the SLD data acquisition system

International Nuclear Information System (INIS)

Nielsen, B.S.

1986-07-01

The data acquisition system for the SLD detector will make extensive use of parallel at the front-end level. Fastbus acquisition modules are being built with powerful processing capabilities for calibration, data reduction and further pre-processing of the large amount of analog data handled by each module. This paper describes the read-out electronics chain and data pre-processing system adapted for most of the detector channels, exemplified by the central drift chamber waveform digitization and processing system

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

Directory of Open Access Journals (Sweden)

Yanlei Li

2015-01-01

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

Salt water intrusion on Uznam Island - 'Wydrzany' water intake

International Nuclear Information System (INIS)

Kochaniec, M.

1999-01-01

Aquifers of Uznam Island have high risk of saline water intrusion due to geographical and geological location. Hydrogeological and geophysical researchers were taken up in order to evaluate changes in intrusion of saline water into aquifer of Uznam Island. Water intake named 'Wydrzany' was built in south part of island in 1973. Since 1975 geophysical research has shown intrusion of salt water from reservoirs and bedrock due to withdrawn of water. In 1997 geoelectrical researches evaluated changes which have taken place since 1975 in saline water intrusion into aquifers of Uznam Island. The last research result showed that intrusion front moved 1100 m to the centre of island in comparison with situation in 1975. (author)

Human intrusion: issues concerning its assessment

International Nuclear Information System (INIS)

Grimwood, P.D.; Smith, G.M.

1989-01-01

The potential significance of human intrusion in the performance assessment of radioactive waste repositories has been increasingly recognized in recent years. It is however an area of assessment in which subjective judgments dominate. This paper identifies some of the issues involved. These include regulatory criteria, scenario development, probability assignment, consequence assessment and measures to mitigate human intrusion

Floor-fractured craters on the Moon: an evidence of past intrusive magmatic activity

Science.gov (United States)

Thorey, C.; Michaut, C.

2012-12-01

's. Given the large number of FFC's observed at the lunar surface, magmatic intrusion seems to be an important process to take into account in lunar geological evolution models as well as to explain geological and geophysical data from the Moon.

Individual differences in spatial configuration learning predict the occurrence of intrusive memories.

Science.gov (United States)

Meyer, Thomas; Smeets, Tom; Giesbrecht, Timo; Quaedflieg, Conny W E M; Girardelli, Marta M; Mackay, Georgina R N; Merckelbach, Harald

2013-03-01

The dual-representation model of posttraumatic stress disorder (PTSD; Brewin, Gregory, Lipton, & Burgess, Psychological Review, 117, 210-232 2010) argues that intrusions occur when people fail to construct context-based representations during adverse experiences. The present study tested a specific prediction flowing from this model. In particular, we investigated whether the efficiency of temporal-lobe-based spatial configuration learning would account for individual differences in intrusive experiences and physiological reactivity in the laboratory. Participants (N = 82) completed the contextual cuing paradigm, which assesses spatial configuration learning that is believed to depend on associative encoding in the parahippocampus. They were then shown a trauma film. Afterward, startle responses were quantified during presentation of trauma reminder pictures versus unrelated neutral and emotional pictures. PTSD symptoms were recorded in the week following participation. Better configuration learning performance was associated with fewer perceptual intrusions, r = -.33, p .46) and had no direct effect on intrusion-related distress and overall PTSD symptoms, rs > -.12, ps > .29. However, configuration learning performance tended to be associated with reduced physiological responses to unrelated negative images, r = -.20, p = .07. Thus, while spatial configuration learning appears to be unrelated to affective responding to trauma reminders, our overall findings support the idea that the context-based memory system helps to reduce intrusions.

Expert judgement on inadvertent human intrusion into the Waste Isolation Pilot Plant

International Nuclear Information System (INIS)

Hora, S.C.; von Winterfeldt, D.; Trauth, K.M.

1991-12-01

Four expert-judgment teams have developed analyses delineating possible future societies in the next 10,000 years in the vicinity of the Waste Isolation Pilot Plant (WIPP). Expert-judgment analysis was used to address the question of future societies because neither experimentation, observation, nor modeling can resolve such uncertainties. Each of the four, four-member teams, comprised of individuals with expertise in the physical, social, or political sciences, developed detailed qualitative assessments of possible future societies. These assessments include detailed discussions of the underlying physical and societal factors that would influence society and the likely modes of human-intrusion at the WIPP, as well as the probabilities of intrusion. Technological development, population growth, economic development, conservation of information, persistence of government control, and mitigation of danger from nuclear waste were the factors the teams believed to be most important. Likely modes of human-intrusion were categorized as excavation, disposal/storage, tunneling, drilling, and offsite activities. Each team also developed quantitative assessments by providing probabilities of various alternative futures, of inadvertent human intrusion, and in some cases, of particular modes of intrusion. The information created throughout this study will be used in conjunction with other types of information, including experimental data, calculations from physical principles and computer models, and perhaps other judgments, as input to ''performance assessment.'' The more qualitative results of this study will be used as input to another expert panel considering markers to deter inadvertent human intrusion at the WIPP

On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear $H_{\\infty}$ Control.

Science.gov (United States)

Wang, Ding; Mu, Chaoxu; Liu, Derong; Ma, Hongwen

2018-04-01

In this paper, based on the adaptive critic learning technique, the control for a class of unknown nonlinear dynamic systems is investigated by adopting a mixed data and event driven design approach. The nonlinear control problem is formulated as a two-player zero-sum differential game and the adaptive critic method is employed to cope with the data-based optimization. The novelty lies in that the data driven learning identifier is combined with the event driven design formulation, in order to develop the adaptive critic controller, thereby accomplishing the nonlinear control. The event driven optimal control law and the time driven worst case disturbance law are approximated by constructing and tuning a critic neural network. Applying the event driven feedback control, the closed-loop system is built with stability analysis. Simulation studies are conducted to verify the theoretical results and illustrate the control performance. It is significant to observe that the present research provides a new avenue of integrating data-based control and event-triggering mechanism into establishing advanced adaptive critic systems.

Water System Adaptation to Hydrological Changes: Module 10, Basic Principles of Incorporating Adaptation Science into Hydrologic Planning and Design

Science.gov (United States)

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

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

CSIR Research Space (South Africa)

Mgabile, T

2012-10-01

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

Magmatic intrusions in the lunar crust

Science.gov (United States)

Michaut, C.; Thorey, C.

2015-10-01

The lunar highlands are very old, with ages covering a timespan between 4.5 to 4.2 Gyr, and probably formed by flotation of light plagioclase minerals on top of the lunar magma ocean. The lunar crust provides thus an invaluable evidence of the geological and magmatic processes occurring in the first times of the terrestrial planets history. According to the last estimates from the GRAIL mission, the lunar primary crust is particularly light and relatively thick [1] This low-density crust acted as a barrier for the dense primary mantle melts. This is particularly evident in the fact that subsequent mare basalts erupted primarily within large impact basin: at least part of the crust must have been removed for the magma to reach the surface. However, the trajectory of the magma from the mantle to the surface is unknown. Using a model of magma emplacement below an elastic overlying layer with a flexural wavelength Λ, we characterize the surface deformations induced by the presence of shallow magmatic intrusions. We demonstrate that, depending on its size, the intrusion can show two different shapes: a bell shape when its radius is smaller than 4 times Λ or a flat top with small bended edges if its radius is larger than 4 times Λ[2]. These characteristic shapes for the intrusion result in characteristic deformations at the surface that also depend on the topography of the layer overlying the intrusion [3].Using this model we provide evidence of the presence of intrusions within the crust of the Moon as surface deformations in the form of low-slope lunar domes and floor-fractured craters. All these geological features have morphologies consistent with models of magma spreading at depth and deforming an overlying elastic layer. Further more,at floor-fractured craters, the deformation is contained within the crater interior, suggesting that the overpressure at the origin of magma ascent and intrusion was less than the pressure due to the weight of the crust removed by

Preliminary evaluation of solution-mining intrusion into a salt-dome repository

International Nuclear Information System (INIS)

1981-06-01

This report is the product of the work of an ONWI task force to evaluate inadvertant human intrusion into a salt dome repository by solution mining. It summarizes the work in the following areas: a general review of the levels of defense that could reduce both the likelihood and potential consequences of human intrusion into a salt dome repository; evaluation of a hypothetical intrusion scenario and its consequences; recommendation for further studies. The conclusions of this task force report can be summarized as follows: (1) it is not possible at present to establish with certainty that solution mining is credible as a human-intrusion event. The likelihood of such an intrusion will depend on the effectiveness of the preventive measures; (2) an example analysis based on the realistic approach is presented in this report; it concluded that the radiological consequences are strongly dependent upon the mode of radionuclide release from the waste form, time after emplacement, package design, impurities in the host salt, the amount of a repository intercepted, the solution mining cavity form, the length of time over which solution mining occurs, the proportion of contaminated salt source for human consumption compared to other sources, and the method of salt purification for culinary purposes; (3) worst case scenarios done by other studies suggest considerable potential for exposures to man while preliminary evaluations of more realistic cases suggest significantly reduced potential consequences. Mathematical model applications to process systems, guided by more advanced assumptions about human intrusion into geomedia, will shed more light on the potential for concerns and the degree to which mitigative measures will be required

Adaptive control of port-Hamiltonian systems

NARCIS (Netherlands)

Dirksz, D.A.; Scherpen, J.M.A.; Edelmayer, András

2010-01-01

In this paper an adaptive control scheme is presented for general port-Hamiltonian systems. Adaptive control is used to compensate for control errors that are caused by unknown or uncertain parameter values of a system. The adaptive control is also combined with canonical transformation theory for

Corticostriatal circuitry in regulating diseases characterized by intrusive thinking.

Science.gov (United States)

Kalivas, Benjamin C; Kalivas, Peter W

2016-03-01

Intrusive thinking triggers clinical symptoms in many neuropsychiatric disorders. Using drug addiction as an exemplar disorder sustained in part by intrusive thinking, we explore studies demonstrating that impairments in corticostriatal circuitry strongly contribute to intrusive thinking. Neuroimaging studies have long implicated this projection in cue-induced craving to use drugs, and preclinical models show that marked changes are produced at corticostriatal synapses in the nucleus accumbens during a relapse episode. We delineate an accumbens microcircuit that mediates cue-induced drug seeking becoming an intrusive event. This microcircuit harbors many potential therapeutic targets. We focus on preclinical and clinical studies, showing that administering N-acetylcysteine restores uptake of synaptic glutamate by astroglial glutamate transporters and thereby inhibits intrusive thinking. We posit that because intrusive thinking is a shared endophenotype in many disorders, N-acetylcysteine has positive effects in clinical trials for a variety of neuropsychiatric disorders, including drug addiction, gambling, trichotillomania, and depression.

Optic Nerve Stimulation System with Adaptive Wireless Powering and Data Telemetry

Directory of Open Access Journals (Sweden)

Xing Li

2017-12-01

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

Biological intrusion of low-level-waste trench covers

Science.gov (United States)

Hakonson, T. E.; Gladney, E. S.

The long-term integrity of low-level waste shallow land burialsites is dependent on the interaction of physical, chemical, and biological factors that modify the waste containment system. The need to consider biological processes as being potentially important in reducing the integrity of waste burial site cover treatment is demonstrated. One approach to limiting biological intrusion through the waste cover is to apply a barrier within the profile to limit root and animal penetration with depth. Experiments in the Los Alamos Experimental Engineered Test Facility were initiated to develop and evaluate biological barriers that are effective in minimizing intrusion into waste trenches. The experiments that are described employ four different candidate barrier materials of geologic origin. Experimental variables that will be evaluated, in addition to barrier type, are barrier depth and sil overburden depth.

FEATURES OF LOGISTIC SYSTEM ADAPTIVE MANAGEMENT

Directory of Open Access Journals (Sweden)

Natalya VOZNENKO

2015-08-01

Full Text Available 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.

Adaptive and non-adaptive data hiding methods for grayscale images based on modulus function

Directory of Open Access Journals (Sweden)

Najme Maleki

2014-07-01

Full Text Available This paper presents two adaptive and non-adaptive data hiding methods for grayscale images based on modulus function. Our adaptive scheme is based on the concept of human vision sensitivity, so the pixels in edge areas than to smooth areas can tolerate much more changes without making visible distortion for human eyes. In our adaptive scheme, the average differencing value of four neighborhood pixels into a block via a threshold secret key determines whether current block is located in edge or smooth area. Pixels in the edge areas are embedded by Q-bit of secret data with a larger value of Q than that of pixels placed in smooth areas. Also in this scholar, we represent one non-adaptive data hiding algorithm. Our non-adaptive scheme, via an error reduction procedure, produces a high visual quality for stego-image. The proposed schemes present several advantages. 1-of aspects the embedding capacity and visual quality of stego-image are scalable. In other words, the embedding rate as well as the image quality can be scaled for practical applications 2-the high embedding capacity with minimal visual distortion can be achieved, 3-our methods require little memory space for secret data embedding and extracting phases, 4-secret keys have used to protect of the embedded secret data. Thus, level of security is high, 5-the problem of overflow or underflow does not occur. Experimental results indicated that the proposed adaptive scheme significantly is superior to the currently existing scheme, in terms of stego-image visual quality, embedding capacity and level of security and also our non-adaptive method is better than other non-adaptive methods, in view of stego-image quality. Results show which our adaptive algorithm can resist against the RS steganalysis attack.

Simulated climate adaptation in storm-water systems: Evaluating the efficiency of within-system flexibility

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Adam D. McCurdy

Full Text Available Changes in regional temperature and precipitation patterns resulting from global climate change may adversely affect the performance of long-lived infrastructure. Adaptation may be necessary to ensure that infrastructure offers consistent service and remains cost effective. But long service times and deep uncertainty associated with future climate projections make adaptation decisions especially challenging for managers. Incorporating flexibility into systems can increase their effectiveness across different climate futures but can also add significant costs. In this paper we review existing work on flexibility in climate change adaptation of infrastructure, such as robust decision-making and dynamic adaptive pathways, apply a basic typology of flexibility, and test alternative strategies for flexibility in distributed infrastructure systems comprised of multiple emplacements of a common, long-lived element: roadway culverts. Rather than treating a system of dispersed infrastructure elements as monolithic, we simulate “options flexibility” in which inherent differences in individual elements is incorporated into adaptation decisions. We use a virtual testbed of highway drainage crossing structures to examine the performance under different climate scenarios of policies that allow for multiple adaptation strategies with varying timing based on individual emplacement characteristics. Results indicate that a strategy with options flexibility informed by crossing characteristics offers a more efficient method of adaptation than do monolithic policies. In some cases this results in more cost-effective adaptation for agencies building long-lived, climate-sensitive infrastructure, even where detailed system data and analytical capacity is limited. Keywords: Climate adaptation, Stormwater management, Adaptation pathways

Episodic intrusion, internal differentiation, and hydrothermal alteration of the miocene tatoosh intrusive suite south of Mount Rainier, Washington

Science.gov (United States)

du Bray, E.A.; Bacon, C.R.; John, D.A.; Wooden, J.L.; Mazdab, F.K.

2011-01-01

The Miocene Tatoosh intrusive suite south of Mount Rainier is composed of three broadly granodioritic plutons that are manifestations of ancestral Cascades arc magmatism. Tatoosh intrusive suite plutons have individually diagnostic characteristics, including texture, mineralogy, and geochemistry, and apparently lack internal contacts. New ion-microprobe U-Pb zircon ages indicate crystallization of the Stevens pluton ca. 19.2 Ma, Reflection-Pyramid pluton ca. 18.5 Ma, and Nisqually pluton ca. 17.5 Ma. The Stevens pluton includes rare, statistically distinct ca. 20.1 Ma zircon antecrysts. Wide-ranging zircon rare earth element (REE), Hf, U, and Th concentrations suggest late crystallization from variably evolved residual liquids. Zircon Eu/Eu*-Hf covariation is distinct for each of the Reflection-Pyramid, Nisqually, and Stevens plutons. Although most Tatoosh intrusive suite rocks have been affected by weak hydrothermal alteration, and sparse mineralized veins cut some of these rocks, significant base or precious metal mineralization is absent. At the time of shallow emplacement, each of these magma bodies was largely homogeneous in bulk composition and petrographic features, but, prior to final solidification, each of the Tatoosh intrusive suite plutons developed internal compositional variation. Geochemical and petrographic trends within each pluton are most consistent with differential loss of residual melt, possibly represented by late aplite dikes or erupted as rhyolite, from crystal-rich magma. Crystal-rich magma that formed each pluton evidently accumulated in reservoirs below the present level of exposure and then intruded to a shallow depth. Assembled by episodic intrusion, the Tatoosh intrusive suite may be representative of midsized composite plutonic complexes beneath arc volcanoes. ?? 2011 Geological Society of America.

Statistical Inference for Data Adaptive Target Parameters.

Science.gov (United States)

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

2016-05-01

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