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)

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

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...

Instant OSSEC host-based intrusion detection system

CERN Document Server

Lhotsky, Brad

2013-01-01

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

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.

Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks

Science.gov (United States)

Zhang, Huibin; Wang, Yuqiao; Chen, Haoran; Zhao, Yongli; Zhang, Jie

2017-12-01

In software defined optical networks (SDON), the centralized control plane may encounter numerous intrusion threatens which compromise the security level of provisioned services. In this paper, the issue of control plane security is studied and two machine-learning-based control plane intrusion detection techniques are proposed for SDON with properly selected features such as bandwidth, route length, etc. We validate the feasibility and efficiency of the proposed techniques by simulations. Results show an accuracy of 83% for intrusion detection can be achieved with the proposed machine-learning-based control plane intrusion detection techniques.

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)

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

A Novel Algorithm for Intrusion Detection Based on RASL Model Checking

Directory of Open Access Journals (Sweden)

Weijun Zhu

2013-01-01

Full Text Available The interval temporal logic (ITL model checking (MC technique enhances the power of intrusion detection systems (IDSs to detect concurrent attacks due to the strong expressive power of ITL. However, an ITL formula suffers from difficulty in the description of the time constraints between different actions in the same attack. To address this problem, we formalize a novel real-time interval temporal logic—real-time attack signature logic (RASL. Based on such a new logic, we put forward a RASL model checking algorithm. Furthermore, we use RASL formulas to describe attack signatures and employ discrete timed automata to create an audit log. As a result, RASL model checking algorithm can be used to automatically verify whether the automata satisfy the formulas, that is, whether the audit log coincides with the attack signatures. The simulation experiments show that the new approach effectively enhances the detection power of the MC-based intrusion detection methods for a number of telnet attacks, p-trace attacks, and the other sixteen types of attacks. And these experiments indicate that the new algorithm can find several types of real-time attacks, whereas the existing MC-based intrusion detection approaches cannot do that.

An Automata Based Intrusion Detection Method for Internet of Things

Directory of Open Access Journals (Sweden)

Yulong Fu

2017-01-01

Full Text Available Internet of Things (IoT transforms network communication to Machine-to-Machine (M2M basis and provides open access and new services to citizens and companies. It extends the border of Internet and will be developed as one part of the future 5G networks. However, as the resources of IoT’s front devices are constrained, many security mechanisms are hard to be implemented to protect the IoT networks. Intrusion detection system (IDS is an efficient technique that can be used to detect the attackers when cryptography is broken, and it can be used to enforce the security of IoT networks. In this article, we analyzed the intrusion detection requirements of IoT networks and then proposed a uniform intrusion detection method for the vast heterogeneous IoT networks based on an automata model. The proposed method can detect and report the possible IoT attacks with three types: jam-attack, false-attack, and reply-attack automatically. We also design an experiment to verify the proposed IDS method and examine the attack of RADIUS application.

Network Intrusion Detection System using Apache Storm

Directory of Open Access Journals (Sweden)

Muhammad Asif Manzoor

2017-06-01

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

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

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

A Protocol Layer Trust-Based Intrusion Detection Scheme for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jian Wang

2017-05-01

Full Text Available This article proposes a protocol layer trust-based intrusion detection scheme for wireless sensor networks. Unlike existing work, the trust value of a sensor node is evaluated according to the deviations of key parameters at each protocol layer considering the attacks initiated at different protocol layers will inevitably have impacts on the parameters of the corresponding protocol layers. For simplicity, the paper mainly considers three aspects of trustworthiness, namely physical layer trust, media access control layer trust and network layer trust. The per-layer trust metrics are then combined to determine the overall trust metric of a sensor node. The performance of the proposed intrusion detection mechanism is then analyzed using the t-distribution to derive analytical results of false positive and false negative probabilities. Numerical analytical results, validated by simulation results, are presented in different attack scenarios. It is shown that the proposed protocol layer trust-based intrusion detection scheme outperforms a state-of-the-art scheme in terms of detection probability and false probability, demonstrating its usefulness for detecting cross-layer attacks.

Real-Time and Resilient Intrusion Detection: A Flow-Based Approach

NARCIS (Netherlands)

Hofstede, R.J.; Pras, Aiko

Due to the demanding performance requirements of packet-based monitoring solutions on network equipment, flow-based intrusion detection systems will play an increasingly important role in current high-speed networks. The required technologies are already available and widely deployed: NetFlow and

Interior intrusion detection systems

Energy Technology Data Exchange (ETDEWEB)

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

1991-10-01

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

Interior intrusion detection systems

International Nuclear Information System (INIS)

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

1991-10-01

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

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.

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

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

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.

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.

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...

An armored-cable-based fiber Bragg grating sensor array for perimeter fence intrusion detection

Science.gov (United States)

Hao, Jianzhong; Dong, Bo; Varghese, Paulose; Phua, Jiliang; Foo, Siang Fook

2012-01-01

In this paper, an armored-cable-based optical fiber Bragg grating (FBG) sensor array, for perimeter fence intrusion detection, is demonstrated and some of the field trial results are reported. The field trial was conducted at a critical local installation in Singapore in December 2010. The sensor array was put through a series of both simulated and live intrusion scenarios to test the stability and suitability of operation in the local environmental conditions and to determine its capabilities in detecting and reporting these intrusions accurately to the control station. Such a sensor array can provide perimeter intrusion detection with fine granularity and preset pin-pointing accuracy. The various types of intrusions included aided or unaided climbs, tampering and cutting of the fence, etc. The unique sensor packaging structure provides high sensitivity, crush resistance and protection against rodents. It is also capable of resolving nuisance events such as rain, birds sitting on the fence or seismic vibrations. These sensors are extremely sensitive with a response time of a few seconds. They can be customized for a desired spatial resolution and pre-determined sensitivity. Furthermore, it is easy to cascade a series of such sensors to monitor and detect intrusion events over a long stretch of fence line. Such sensors can be applied to real-time intrusion detection for perimeter security, pipeline security and communications link security.

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.

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

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.

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.

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.

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.

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.

Intrusion detection in cloud computing based attack patterns and risk assessment

Directory of Open Access Journals (Sweden)

Ben Charhi Youssef

2017-05-01

Full Text Available This paper is an extension of work originally presented in SYSCO CONF.We extend our previous work by presenting the initial results of the implementation of intrusion detection based on risk assessment on cloud computing. The idea focuses on a novel approach for detecting cyber-attacks on the cloud environment by analyzing attacks pattern using risk assessment methodologies. The aim of our solution is to combine evidences obtained from Intrusion Detection Systems (IDS deployed in a cloud with risk assessment related to each attack pattern. Our approach presents a new qualitative solution for analyzing each symptom, indicator and vulnerability analyzing impact and likelihood of distributed and multi-steps attacks directed to cloud environments. The implementation of this approach will reduce the number of false alerts and will improve the performance of the IDS.

A two-stage flow-based intrusion detection model for next-generation networks.

Science.gov (United States)

Umer, Muhammad Fahad; Sher, Muhammad; Bi, Yaxin

2018-01-01

The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results.

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.

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.

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

Science.gov (United States)

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

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.

Developing advanced fingerprint attacks on challenge-based collaborative intrusion detection networks

DEFF Research Database (Denmark)

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

2017-01-01

Traditionally, an isolated intrusion detection system (IDS) is vulnerable to various types of attacks. In order to enhance IDS performance, collaborative intrusion detection networks (CIDNs) are developed through enabling a set of IDS nodes to communicate with each other. Due to the distributed...... network architecture, insider attacks are one of the major threats. In the literature, challenge-based trust mechanisms have been built to identify malicious nodes by evaluating the satisfaction levels between challenges and responses. However, such mechanisms rely on two major assumptions, which may...... result in a weak threat model. In this case, CIDNs may be still vulnerable to advanced insider attacks in real-world deployment. In this paper, we propose a novel collusion attack, called passive message fingerprint attack (PMFA), which can collect messages and identify normal requests in a passive way...

SOOA: Exploring Special On-Off Attacks on Challenge-Based Collaborative Intrusion Detection Networks

DEFF Research Database (Denmark)

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

2017-01-01

The development of collaborative intrusion detection networks (CIDNs) aims to enhance the performance of a single intrusion detection system (IDS), through communicating and collecting information from other IDS nodes. To defend CIDNs against insider attacks, trust-based mechanisms are crucial...... and render CIDNs still vulnerable to advanced insider attacks in a practical deployment. In this paper, our motivation is to investigate the effect of On-Off attacks on challenge-based CIDNs. In particular, as a study, we explore a special On-Off attack (called SOOA), which can keep responding normally...... to one node while acting abnormally to another node. In the evaluation, we explore the attack performance under simulated CIDN environments. Experimental results indicate that our attack can interfere the effectiveness of trust computation for CIDN nodes....

Feature selection for anomaly–based network intrusion detection using cluster validity indices

CSIR Research Space (South Africa)

Naidoo, T

2015-09-01

Full Text Available for Anomaly–Based Network Intrusion Detection Using Cluster Validity Indices Tyrone Naidoo_, Jules–Raymond Tapamoy, Andre McDonald_ Modelling and Digital Science, Council for Scientific and Industrial Research, South Africa 1tnaidoo2@csir.co.za 3...

Case-Based Multi-Sensor Intrusion Detection

Science.gov (United States)

Schwartz, Daniel G.; Long, Jidong

2009-08-01

Multi-sensor intrusion detection systems (IDSs) combine the alerts raised by individual IDSs and possibly other kinds of devices such as firewalls and antivirus software. A critical issue in building a multi-sensor IDS is alert-correlation, i.e., determining which alerts are caused by the same attack. This paper explores a novel approach to alert correlation using case-based reasoning (CBR). Each case in the CBR system's library contains a pattern of alerts raised by some known attack type, together with the identity of the attack. Then during run time, the alert streams gleaned from the sensors are compared with the patterns in the cases, and a match indicates that the attack described by that case has occurred. For this purpose the design of a fast and accurate matching algorithm is imperative. Two such algorithms were explored: (i) the well-known Hungarian algorithm, and (ii) an order-preserving matching of our own device. Tests were conducted using the DARPA Grand Challenge Problem attack simulator. These showed that the both matching algorithms are effective in detecting attacks; but the Hungarian algorithm is inefficient; whereas the order-preserving one is very efficient, in fact runs in linear time.

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.

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.

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.

Ensemble regression model-based anomaly detection for cyber-physical intrusion detection in smart grids

DEFF Research Database (Denmark)

Kosek, Anna Magdalena; Gehrke, Oliver

2016-01-01

The shift from centralised large production to distributed energy production has several consequences for current power system operation. The replacement of large power plants by growing numbers of distributed energy resources (DERs) increases the dependency of the power system on small scale......, distributed production. Many of these DERs can be accessed and controlled remotely, posing a cybersecurity risk. This paper investigates an intrusion detection system which evaluates the DER operation in order to discover unauthorized control actions. The proposed anomaly detection method is based...

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.

The Use of Artificial-Intelligence-Based Ensembles for Intrusion Detection: A Review

Directory of Open Access Journals (Sweden)

Gulshan Kumar

2012-01-01

Full Text Available In supervised learning-based classification, ensembles have been successfully employed to different application domains. In the literature, many researchers have proposed different ensembles by considering different combination methods, training datasets, base classifiers, and many other factors. Artificial-intelligence-(AI- based techniques play prominent role in development of ensemble for intrusion detection (ID and have many benefits over other techniques. However, there is no comprehensive review of ensembles in general and AI-based ensembles for ID to examine and understand their current research status to solve the ID problem. Here, an updated review of ensembles and their taxonomies has been presented in general. The paper also presents the updated review of various AI-based ensembles for ID (in particular during last decade. The related studies of AI-based ensembles are compared by set of evaluation metrics driven from (1 architecture & approach followed; (2 different methods utilized in different phases of ensemble learning; (3 other measures used to evaluate classification performance of the ensembles. The paper also provides the future directions of the research in this area. The paper will help the better understanding of different directions in which research of ensembles has been done in general and specifically: field of intrusion detection systems (IDSs.

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...

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.

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.

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

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

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.

FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET.

Science.gov (United States)

N Ahmed, Malik; Abdullah, Abdul Hanan; Kaiwartya, Omprakash

2016-01-01

Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks.

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.

Multilayer Statistical Intrusion Detection in Wireless Networks

Science.gov (United States)

Hamdi, Mohamed; Meddeb-Makhlouf, Amel; Boudriga, Noureddine

2008-12-01

The rapid proliferation of mobile applications and services has introduced new vulnerabilities that do not exist in fixed wired networks. Traditional security mechanisms, such as access control and encryption, turn out to be inefficient in modern wireless networks. Given the shortcomings of the protection mechanisms, an important research focuses in intrusion detection systems (IDSs). This paper proposes a multilayer statistical intrusion detection framework for wireless networks. The architecture is adequate to wireless networks because the underlying detection models rely on radio parameters and traffic models. Accurate correlation between radio and traffic anomalies allows enhancing the efficiency of the IDS. A radio signal fingerprinting technique based on the maximal overlap discrete wavelet transform (MODWT) is developed. Moreover, a geometric clustering algorithm is presented. Depending on the characteristics of the fingerprinting technique, the clustering algorithm permits to control the false positive and false negative rates. Finally, simulation experiments have been carried out to validate the proposed IDS.

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

FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET.

Directory of Open Access Journals (Sweden)

Malik N Ahmed

Full Text Available Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks.

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...

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

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...

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....

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

Directory of Open Access Journals (Sweden)

Rupinder Singh

2017-01-01

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

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 ...

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.

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.

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.

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. ...

Use of behavioral biometrics in intrusion detection and online gaming

Science.gov (United States)

Yampolskiy, Roman V.; Govindaraju, Venu

2006-04-01

Behavior based intrusion detection is a frequently used approach for insuring network security. We expend behavior based intrusion detection approach to a new domain of game networks. Specifically, our research shows that a unique behavioral biometric can be generated based on the strategy used by an individual to play a game. We wrote software capable of automatically extracting behavioral profiles for each player in a game of Poker. Once a behavioral signature is generated for a player, it is continuously compared against player's current actions. Any significant deviations in behavior are reported to the game server administrator as potential security breaches. Our algorithm addresses a well-known problem of user verification and can be re-applied to the fields beyond game networks, such as operating systems and non-game networks security.

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.

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 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

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...

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.

Towards Reliable Evaluation of Anomaly-Based Intrusion Detection Performance

Science.gov (United States)

Viswanathan, Arun

2012-01-01

This report describes the results of research into the effects of environment-induced noise on the evaluation process for anomaly detectors in the cyber security domain. This research was conducted during a 10-week summer internship program from the 19th of August, 2012 to the 23rd of August, 2012 at the Jet Propulsion Laboratory in Pasadena, California. The research performed lies within the larger context of the Los Angeles Department of Water and Power (LADWP) Smart Grid cyber security project, a Department of Energy (DoE) funded effort involving the Jet Propulsion Laboratory, California Institute of Technology and the University of Southern California/ Information Sciences Institute. The results of the present effort constitute an important contribution towards building more rigorous evaluation paradigms for anomaly-based intrusion detectors in complex cyber physical systems such as the Smart Grid. Anomaly detection is a key strategy for cyber intrusion detection and operates by identifying deviations from profiles of nominal behavior and are thus conceptually appealing for detecting "novel" attacks. Evaluating the performance of such a detector requires assessing: (a) how well it captures the model of nominal behavior, and (b) how well it detects attacks (deviations from normality). Current evaluation methods produce results that give insufficient insight into the operation of a detector, inevitably resulting in a significantly poor characterization of a detectors performance. In this work, we first describe a preliminary taxonomy of key evaluation constructs that are necessary for establishing rigor in the evaluation regime of an anomaly detector. We then focus on clarifying the impact of the operational environment on the manifestation of attacks in monitored data. We show how dynamic and evolving environments can introduce high variability into the data stream perturbing detector performance. Prior research has focused on understanding the impact of this

PMFA: Toward Passive Message Fingerprint Attacks on Challenge-Based Collaborative Intrusion Detection Networks

DEFF Research Database (Denmark)

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

2016-01-01

To enhance the performance of single intrusion detection systems (IDSs), collaborative intrusion detection networks (CIDNs) have been developed, which enable a set of IDS nodes to communicate with each other. In such a distributed network, insider attacks like collusion attacks are the main threat...... to advanced insider attacks in practical deployment. In this paper, we design a novel type of collusion attack, called passive message fingerprint attack (PMFA), which can collect messages and identify normal requests in a passive way. In the evaluation, we explore the attack performance under both simulated...... and real network environments. Experimental results indicate that under our attack, malicious nodes can send malicious responses to normal requests while maintaining their trust values....

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

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...

DFCL: DYNAMIC FUZZY LOGIC CONTROLLER FOR INTRUSION DETECTION

Directory of Open Access Journals (Sweden)

Abdulrahim Haroun Ali

2014-08-01

Full Text Available Intrusions are a problem with the deployment of Networks which give misuse and abnormal behavior in running reliable network operations and services. In this work, a Dynamic Fuzzy Logic Controller (DFLC is proposed for an anomaly detection problem, with the aim of solving the problem of attack detection rate and faster response process. Data is collected by PingER project. PingER project actively measures the worldwide Internet’s end-to-end performance. It covers over 168 countries around the world. PingER uses simple ubiquitous Internet Ping facility to calculate number of useful performance parameters. From each set of 10 pings between a monitoring host and a remote host, the features being calculated include Minimum Round Trip Time (RTT, Jitter, Packet loss, Mean Opinion Score (MOS, Directness of Connection (Alpha, Throughput, ping unpredictability and ping reachability. A set of 10 pings is being sent from the monitoring node to the remote node every 30 minutes. The received data shows the current characteristic and behavior of the networks. Any changes in the received data signify the existence of potential threat or abnormal behavior. D-FLC uses the combination of parameters as an input to detect the existence of any abnormal behavior of the network. The proposed system is simulated in Matlab Simulink environment. Simulations results show that the system managed to catch 95% of the anomalies with the ability to distinguish normal and abnormal behavior of the network.

An evaluation of classification algorithms for intrusion detection ...

African Journals Online (AJOL)

An evaluation of classification algorithms for intrusion detection. ... Log in or Register to get access to full text downloads. ... Most of the available IDSs use all the 41 features in the network to evaluate and search for intrusive pattern in which ...

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...

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.

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.

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...

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

Detecting peripheral-based attacks on the host memory

CERN Document Server

Stewin, Patrick

2015-01-01

This work addresses stealthy peripheral-based attacks on host computers and presents a new approach to detecting them. Peripherals can be regarded as separate systems that have a dedicated processor and dedicated runtime memory to handle their tasks. The book addresses the problem that peripherals generally communicate with the host via the host’s main memory, storing cryptographic keys, passwords, opened files and other sensitive data in the process – an aspect attackers are quick to exploit.  Here, stealthy malicious software based on isolated micro-controllers is implemented to conduct an attack analysis, the results of which provide the basis for developing a novel runtime detector. The detector reveals stealthy peripheral-based attacks on the host’s main memory by exploiting certain hardware properties, while a permanent and resource-efficient measurement strategy ensures that the detector is also capable of detecting transient attacks, which can otherwise succeed when the applied strategy only me...

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.

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

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

Multi-User Low Intrusive Occupancy Detection.

Science.gov (United States)

Pratama, Azkario Rizky; Widyawan, Widyawan; Lazovik, Alexander; Aiello, Marco

2018-03-06

Smart spaces are those that are aware of their state and can act accordingly. Among the central elements of such a state is the presence of humans and their number. For a smart office building, such information can be used for saving energy and safety purposes. While acquiring presence information is crucial, using sensing techniques that are highly intrusive, such as cameras, is often not acceptable for the building occupants. In this paper, we illustrate a proposal for occupancy detection which is low intrusive; it is based on equipment typically available in modern offices such as room-level power-metering and an app running on workers' mobile phones. For power metering, we collect the aggregated power consumption and disaggregate the load of each device. For the mobile phone, we use the Received Signal Strength (RSS) of BLE (Bluetooth Low Energy) nodes deployed around workspaces to localize the phone in a room. We test the system in our offices. The experiments show that sensor fusion of the two sensing modalities gives 87-90% accuracy, demonstrating the effectiveness of the proposed approach.

Multi-User Low Intrusive Occupancy Detection

Science.gov (United States)

Widyawan, Widyawan; Lazovik, Alexander

2018-01-01

Smart spaces are those that are aware of their state and can act accordingly. Among the central elements of such a state is the presence of humans and their number. For a smart office building, such information can be used for saving energy and safety purposes. While acquiring presence information is crucial, using sensing techniques that are highly intrusive, such as cameras, is often not acceptable for the building occupants. In this paper, we illustrate a proposal for occupancy detection which is low intrusive; it is based on equipment typically available in modern offices such as room-level power-metering and an app running on workers’ mobile phones. For power metering, we collect the aggregated power consumption and disaggregate the load of each device. For the mobile phone, we use the Received Signal Strength (RSS) of BLE (Bluetooth Low Energy) nodes deployed around workspaces to localize the phone in a room. We test the system in our offices. The experiments show that sensor fusion of the two sensing modalities gives 87–90% accuracy, demonstrating the effectiveness of the proposed approach. PMID:29509693

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...

Towards effective and robust list-based packet filter for signature-based network intrusion detection: an engineering approach

DEFF Research Database (Denmark)

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

2017-01-01

Network intrusion detection systems (NIDSs) which aim to identify various attacks, have become an essential part of current security infrastructure. In particular, signature-based NIDSs are being widely implemented in industry due to their low rate of false alarms. However, the signature matching...... this problem, packet filtration is a promising solution to reduce unwanted traffic. Motivated by this, in this work, a list-based packet filter was designed and an engineering method of combining both blacklist and whitelist techniques was introduced. To further secure such filters against IP spoofing attacks...... in traffic filtration as well as workload reduction, and is robust against IP spoofing attacks....

Attacks and Intrusion Detection in Cloud Computing Using Neural Networks and Particle Swarm Optimization Algorithms

Directory of Open Access Journals (Sweden)

Ahmad Shokuh Saljoughi

2018-01-01

Full Text Available Today, cloud computing has become popular among users in organizations and companies. Security and efficiency are the two major issues facing cloud service providers and their customers. Since cloud computing is a virtual pool of resources provided in an open environment (Internet, cloud-based services entail security risks. Detection of intrusions and attacks through unauthorized users is one of the biggest challenges for both cloud service providers and cloud users. In the present study, artificial intelligence techniques, e.g. MLP Neural Network sand particle swarm optimization algorithm, were used to detect intrusion and attacks. The methods were tested for NSL-KDD, KDD-CUP datasets. The results showed improved accuracy in detecting attacks and intrusions by unauthorized users.

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

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.

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

Multi-User Low Intrusive Occupancy Detection

Directory of Open Access Journals (Sweden)

Azkario Rizky Pratama

2018-03-01

Full Text Available Smart spaces are those that are aware of their state and can act accordingly. Among the central elements of such a state is the presence of humans and their number. For a smart office building, such information can be used for saving energy and safety purposes. While acquiring presence information is crucial, using sensing techniques that are highly intrusive, such as cameras, is often not acceptable for the building occupants. In this paper, we illustrate a proposal for occupancy detection which is low intrusive; it is based on equipment typically available in modern offices such as room-level power-metering and an app running on workers’ mobile phones. For power metering, we collect the aggregated power consumption and disaggregate the load of each device. For the mobile phone, we use the Received Signal Strength (RSS of BLE (Bluetooth Low Energy nodes deployed around workspaces to localize the phone in a room. We test the system in our offices. The experiments show that sensor fusion of the two sensing modalities gives 87–90% accuracy, demonstrating the effectiveness of the proposed approach.

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

An Adaptive Database Intrusion Detection System

Science.gov (United States)

Barrios, Rita M.

2011-01-01

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

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

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.

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.

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.

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

Science.gov (United States)

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

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.

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.

Unconventional applications of conventional intrusion detection sensors

International Nuclear Information System (INIS)

Williams, J.D.; Matter, J.C.

1983-01-01

A number of conventional intrusion detection sensors exists for the detection of persons entering buildings, moving within a given volume, and crossing a perimeter isolation zone. Unconventional applications of some of these sensors have recently been investigated. Some of the applications which are discussed include detection on the edges and tops of buildings, detection in storm sewers, detection on steam and other types of large pipes, and detection of unauthorized movement within secure enclosures. The enclosures can be used around complicated control valves, electrical control panels, emergency generators, etc

基于信息熵的SVM入侵检测技术%Exploring SVM-based intrusion detection through information entropy theory

Institute of Scientific and Technical Information of China (English)

朱文杰; 王强; 翟献军

2013-01-01

在传统基于SVM的入侵检测中,核函数构造和特征选择采用先验知识,普遍存在准确度不高、效率低下的问题.通过信息熵理论与SVM算法相结合的方法改进为基于信息熵的SVM入侵检测算法,可以提高入侵检测的准确性,提升入侵检测的效率.基于信息熵的SVM入侵检测算法包括两个方面:一方面,根据样本包含的用户信息熵和方差,将样本特征统一,以特征是否属于置信区间来度量.将得到的样本特征置信向量作为SVM核函数的构造参数,既可保证训练样本集与最优分类面之间的对应关系,又可得到入侵检测需要的最大分类间隔；另一方面,将样本包含的用户信息量作为度量大幅度约简样本特征子集,不但降低了样本计算规模,而且提高了分类器的训练速度.实验表明,该算法在入侵检测系统中的应用优于传统的SVM算法.%In traditional SVM based intrusion detection approaches,both core function construction and feature selection use prior knowdege.Due to this,they are not only inefficient but also inaccurate.It is observed that integrating information entropy theory into SVM-based intrusion detection can enhance both the precision and the speed.Concludely speaking,SVM-based entropy intrusion detection algorithms are made up of two aspects:on one hand,setting sample confidence vector as core function's constructor of SVM algorithm can guarantee the mapping relationship between training sample and optimization classification plane.Also,the intrusion detection's maximum interval can be acquired.On the other hand,simplifying feature subset with samples's entropy as metric standard can not only shrink the computing scale but also improve the speed.Experiments prove that the SVM based entropy intrusion detection algoritm outperfomrs other tradional algorithms.

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)

Access Control from an Intrusion Detection Perspective

NARCIS (Netherlands)

Nunes Leal Franqueira, V.

Access control and intrusion detection are essential components for securing an organization's information assets. In practice, these components are used in isolation, while their fusion would contribute to increase the range and accuracy of both. One approach to accomplish this fusion is the

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.

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...

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

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.

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.

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...

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.

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.

Wireless sensing without sensors—an experimental study of motion/intrusion detection using RF irregularity

International Nuclear Information System (INIS)

Lee, Pius W Q; Tan, Hwee-Pink; Seah, Winston K G; Yao, Zexi

2010-01-01

Motion and intrusion detection are often cited as wireless sensor network (WSN) applications with typical configurations comprising clusters of wireless nodes equipped with motion sensors to detect human motion. Currently, WSN performance is subjected to several constraints, namely radio irregularity and finite on-board computation/energy resources. Radio irregularity in radio frequency (RF) propagation rises to a higher level in the presence of human activity due to the absorption effect of the human body. In this paper, we investigate the feasibility of monitoring RF transmission for the purpose of intrusion detection through experimentation. With empirical data obtained from the Crossbow TelosB platform in several different environments, the impact of human activity on the signal strength of RF signals in a WSN is evaluated. We then propose a novel approach to intrusion detection by turning a constraint in WSN, namely radio irregularity, into an advantage for the purpose of intrusion detection, using signal fluctuations to detect the presence of human activity within the WSN. Unlike RF fingerprinting, the 'intruders' here neither transmit nor receive any RF signals. By enabling existing wireless infrastructures to serve as intrusion detectors instead of deploying numerous costly sensors, this approach shows great promise for providing novel solutions

A Distributed Intrusion Detection Scheme about Communication Optimization in Smart Grid

Directory of Open Access Journals (Sweden)

Yunfa Li

2013-01-01

Full Text Available We first propose an efficient communication optimization algorithm in smart grid. Based on the optimization algorithm, we propose an intrusion detection algorithm to detect malicious data and possible cyberattacks. In this scheme, each node acts independently when it processes communication flows or cybersecurity threats. And neither special hardware nor nodes cooperation is needed. In order to justify the feasibility and the availability of this scheme, a series of experiments have been done. The results show that it is feasible and efficient to detect malicious data and possible cyberattacks with less computation and communication cost.

State of the Practice of Intrusion Detection Technologies

Science.gov (United States)

2000-01-01

functions, procedures, and scripts, an Oracle database structure, Borne shell scripts, and configuration files which together communicate with ASIM Sensor...34Plugging the Holes in eCommerce Leads to 135% Growth in the Intrusion Detection and Vulnerability Assessment Software Market," PRNewswire. August

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

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...

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.

A New Unified Intrusion Anomaly Detection in Identifying Unseen Web Attacks

Directory of Open Access Journals (Sweden)

Muhammad Hilmi Kamarudin

2017-01-01

Full Text Available The global usage of more sophisticated web-based application systems is obviously growing very rapidly. Major usage includes the storing and transporting of sensitive data over the Internet. The growth has consequently opened up a serious need for more secured network and application security protection devices. Security experts normally equip their databases with a large number of signatures to help in the detection of known web-based threats. In reality, it is almost impossible to keep updating the database with the newly identified web vulnerabilities. As such, new attacks are invisible. This research presents a novel approach of Intrusion Detection System (IDS in detecting unknown attacks on web servers using the Unified Intrusion Anomaly Detection (UIAD approach. The unified approach consists of three components (preprocessing, statistical analysis, and classification. Initially, the process starts with the removal of irrelevant and redundant features using a novel hybrid feature selection method. Thereafter, the process continues with the application of a statistical approach to identifying traffic abnormality. We performed Relative Percentage Ratio (RPR coupled with Euclidean Distance Analysis (EDA and the Chebyshev Inequality Theorem (CIT to calculate the normality score and generate a finest threshold. Finally, Logitboost (LB is employed alongside Random Forest (RF as a weak classifier, with the aim of minimising the final false alarm rate. The experiment has demonstrated that our approach has successfully identified unknown attacks with greater than a 95% detection rate and less than a 1% false alarm rate for both the DARPA 1999 and the ISCX 2012 datasets.

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.

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...

Improving Accuracy of Intrusion Detection Model Using PCA and optimized SVM

Directory of Open Access Journals (Sweden)

Sumaiya Thaseen Ikram

2016-06-01

Full Text Available Intrusion detection is very essential for providing security to different network domains and is mostly used for locating and tracing the intruders. There are many problems with traditional intrusion detection models (IDS such as low detection capability against unknown network attack, high false alarm rate and insufficient analysis capability. Hence the major scope of the research in this domain is to develop an intrusion detection model with improved accuracy and reduced training time. This paper proposes a hybrid intrusiondetection model by integrating the principal component analysis (PCA and support vector machine (SVM. The novelty of the paper is the optimization of kernel parameters of the SVM classifier using automatic parameter selection technique. This technique optimizes the punishment factor (C and kernel parameter gamma (γ, thereby improving the accuracy of the classifier and reducing the training and testing time. The experimental results obtained on the NSL KDD and gurekddcup dataset show that the proposed technique performs better with higher accuracy, faster convergence speed and better generalization. Minimum resources are consumed as the classifier input requires reduced feature set for optimum classification. A comparative analysis of hybrid models with the proposed model is also performed.

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

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.

A host-guest-recognition-based electrochemical aptasensor for thrombin detection.

Science.gov (United States)

Fan, Hao; Li, Hui; Wang, Qingjiang; He, Pingang; Fang, Yuzhi

2012-05-15

A sensitive electrochemical aptasensor for thrombin detection is presented based on the host-guest recognition technique. In this sensing protocol, a 15 based thrombin aptamer (ab. TBA) was dually labeled with a thiol at its 3' end and a 4-((4-(dimethylamino)phenyl)azo) benzoic acid (dabcyl) at its 5' end, respectively, which was previously immobilized on one Au electrode surface by AuS bond and used as the thrombin probe during the protein sensing procedure. One special electrochemical marker was prepared by modifying CdS nanoparticle with β-cyclodextrins (ab. CdS-CDs), which employed as electrochemical signal provider and would conjunct with the thrombin probe modified electrode through the host-guest recognition of CDs to dabcyl. In the absence of thrombin, the probe adopted linear structure to conjunct with CdS-CDs. In present of thrombin, the TBA bond with thrombin and transformed into its special G-quarter structure, which forced CdS-CDs into the solution. Therefore, the target-TBA binding event can be sensitively transduced via detecting the electrochemical oxidation current signal of Cd of CdS nanoparticles in the solution. Using this method, as low as 4.6 pM thrombin had been detected. Copyright © 2012 Elsevier B.V. All rights reserved.

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

Directory of Open Access Journals (Sweden)

P. Amudha

2015-01-01

Full Text Available Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC with Enhanced Particle Swarm Optimization (EPSO to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup’99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different.

Towards real-time intrusion detection for NetFlow and IPFIX

NARCIS (Netherlands)

Hofstede, R.J.; Bartos, Vaclav; Sperotto, Anna; Pras, Aiko

2013-01-01

DDoS attacks bring serious economic and technical damage to networks and enterprises. Timely detection and mitigation are therefore of great importance. However, when flow monitoring systems are used for intrusion detection, as it is often the case in campus, enterprise and backbone networks, timely

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

A Comprehensive Review and meta-analysis on Applications of Machine Learning Techniques in Intrusion Detection

Directory of Open Access Journals (Sweden)

Manojit Chattopadhyay

2018-05-01

Full Text Available Securing a machine from various cyber-attacks has been of serious concern for researchers, statutory bodies such as governments, business organizations and users in both wired and wireless media. However, during the last decade, the amount of data handling by any device, particularly servers, has increased exponentially and hence the security of these devices has become a matter of utmost concern. This paper attempts to examine the challenges in the application of machine learning techniques to intrusion detection. We review different inherent issues in defining and applying the machine learning techniques to intrusion detection. We also attempt to identify the best technological solution for changing usage pattern by comparing different machine learning techniques on different datasets and summarizing their performance using various performance metrics. This paper highlights the research challenges and future trends of intrusion detection in dynamic scenarios of intrusion detection problems in diverse network technologies.

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...

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

KAUST Repository

Wang, Wei; Guyet, Thomas; Quiniou, René ; Cordier, Marie-Odile; Masseglia, Florent; Zhang, Xiangliang

2014-01-01

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

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

KAUST Repository

Wang, Wei

2014-06-22

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

Accurate Modeling of The Siemens S7 SCADA Protocol For Intrusion Detection And Digital Forensic

Directory of Open Access Journals (Sweden)

Amit Kleinmann

2014-09-01

Full Text Available The Siemens S7 protocol is commonly used in SCADA systems for communications between a Human Machine Interface (HMI and the Programmable Logic Controllers (PLCs. This paper presents a model-based Intrusion Detection Systems (IDS designed for S7 networks. The approach is based on the key observation that S7 traffic to and from a specific PLC is highly periodic; as a result, each HMI-PLC channel can be modeled using its own unique Deterministic Finite Automaton (DFA. The resulting DFA-based IDS is very sensitive and is able to flag anomalies such as a message appearing out of its position in the normal sequence or a message referring to a single unexpected bit. The intrusion detection approach was evaluated on traffic from two production systems. Despite its high sensitivity, the system had a very low false positive rate - over 99.82% of the traffic was identified as normal.

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.

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...

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.

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

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

Science.gov (United States)

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

2017-01-01

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

Correlating intrusion detection alerts on bot malware infections using neural network

DEFF Research Database (Denmark)

Kidmose, Egon; Stevanovic, Matija; Pedersen, Jens Myrup

2016-01-01

Millions of computers are infected with bot malware, form botnets and enable botmaster to perform malicious and criminal activities. Intrusion Detection Systems are deployed to detect infections, but they raise many correlated alerts for each infection, requiring a large manual investigation effort...

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.

Prototype of Intrusion Detection Model using UML 5.0 and Forward Engineering

Directory of Open Access Journals (Sweden)

Muthaiyan MADIAJAGAN,

2011-01-01

Full Text Available In this paper we are using UML (Unified Modeling Language which is the blueprint language between the programmers, analysts, and designer’s for easy representation of pictures or diagrammatic notation with some textual data. Here we are using UML 5.0 to show “prototype of the Intrusion Detection Model” and by explaining it by combining various parts by drawing various UML diagrams such as Use cases and Activity diagrams and Class Diagram using which we show forward engineering using the class diagram of the IDM( Intrusion Detection Model. IDM is a device or software that works on detecting malicious activities by unauthorized users that can cause breach to the security policy within a network.

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.

QOS and Control-Theoretic Techniques for Intrusion Tolerance

National Research Council Canada - National Science Library

Ye, Nong

2004-01-01

...), even in the face of intrusions. This report examines two host-based resources, a router and a web server, and presents simulated models of modifications that can be made to these resources to make them QoS-capable...

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 ...

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.

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...

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

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

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.

Intrusion of Magmatic Bodies Into the Continental Crust: 3-D Numerical Models

Science.gov (United States)

Gorczyk, Weronika; Vogt, Katharina

2018-03-01

Magma intrusion is a major material transfer process in the Earth's continental crust. Yet the mechanical behavior of the intruding magma and its host are a matter of debate. In this study we present a series of numerical thermomechanical simulations on magma emplacement in 3-D. Our results demonstrate the response of the continental crust to magma intrusion. We observe change in intrusion geometries between dikes, cone sheets, sills, plutons, ponds, funnels, finger-shaped and stock-like intrusions, and injection time. The rheology and temperature of the host are the main controlling factors in the transition between these different modes of intrusion. Viscous deformation in the warm and deep crust favors host rock displacement and plutons at the crust-mantle boundary forming deep-seated plutons or magma ponds in the lower to middle crust. Brittle deformation in the cool and shallow crust induces cone-shaped fractures in the host rock and enables emplacement of finger- or stock-like intrusions at shallow or intermediate depth. Here the passage of magmatic and hydrothermal fluids from the intrusion through the fracture pattern may result in the formation of ore deposits. A combination of viscous and brittle deformation forms funnel-shaped intrusions in the middle crust. Intrusion of low-density magma may more over result in T-shaped intrusions in cross section with magma sheets at the surface.

Profile-based adaptive anomaly detection for network security.

Energy Technology Data Exchange (ETDEWEB)

Zhang, Pengchu C. (Sandia National Laboratories, Albuquerque, NM); Durgin, Nancy Ann

2005-11-01

As information systems become increasingly complex and pervasive, they become inextricably intertwined with the critical infrastructure of national, public, and private organizations. The problem of recognizing and evaluating threats against these complex, heterogeneous networks of cyber and physical components is a difficult one, yet a solution is vital to ensuring security. In this paper we investigate profile-based anomaly detection techniques that can be used to address this problem. We focus primarily on the area of network anomaly detection, but the approach could be extended to other problem domains. We investigate using several data analysis techniques to create profiles of network hosts and perform anomaly detection using those profiles. The ''profiles'' reduce multi-dimensional vectors representing ''normal behavior'' into fewer dimensions, thus allowing pattern and cluster discovery. New events are compared against the profiles, producing a quantitative measure of how ''anomalous'' the event is. Most network intrusion detection systems (IDSs) detect malicious behavior by searching for known patterns in the network traffic. This approach suffers from several weaknesses, including a lack of generalizability, an inability to detect stealthy or novel attacks, and lack of flexibility regarding alarm thresholds. Our research focuses on enhancing current IDS capabilities by addressing some of these shortcomings. We identify and evaluate promising techniques for data mining and machine-learning. The algorithms are ''trained'' by providing them with a series of data-points from ''normal'' network traffic. A successful algorithm can be trained automatically and efficiently, will have a low error rate (low false alarm and miss rates), and will be able to identify anomalies in ''pseudo real-time'' (i.e., while the intrusion is still in progress

Quality-of-service sensitivity to bio-inspired/evolutionary computational methods for intrusion detection in wireless ad hoc multimedia sensor networks

Science.gov (United States)

Hortos, William S.

2012-06-01

In the author's previous work, a cross-layer protocol approach to wireless sensor network (WSN) intrusion detection an identification is created with multiple bio-inspired/evolutionary computational methods applied to the functions of the protocol layers, a single method to each layer, to improve the intrusion-detection performance of the protocol over that of one method applied to only a single layer's functions. The WSN cross-layer protocol design embeds GAs, anti-phase synchronization, ACO, and a trust model based on quantized data reputation at the physical, MAC, network, and application layer, respectively. The construct neglects to assess the net effect of the combined bioinspired methods on the quality-of-service (QoS) performance for "normal" data streams, that is, streams without intrusions. Analytic expressions of throughput, delay, and jitter, coupled with simulation results for WSNs free of intrusion attacks, are the basis for sensitivity analyses of QoS metrics for normal traffic to the bio-inspired methods.

The Monitoring, Detection, Isolation and Assessment of Information Warfare Attacks Through Multi-Level, Multi-Scale System Modeling and Model Based Technology

Science.gov (United States)

2004-01-01

login identity to the one under which the system call is executed, the parameters of the system call execution - file names including full path...Anomaly detection COAST-EIMDT Distributed on target hosts EMERALD Distributed on target hosts and security servers Signature recognition Anomaly...uses a centralized architecture, and employs an anomaly detection technique for intrusion detection. The EMERALD project [80] proposes a

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.

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

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.

Effective approach toward Intrusion Detection System using data mining techniques

Directory of Open Access Journals (Sweden)

G.V. Nadiammai

2014-03-01

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

Energy Efficient Monitoring for Intrusion Detection in Battery-Powered Wireless Mesh Networks

KAUST Repository

Hassanzadeh, Amin

2011-07-18

Wireless Mesh Networks (WMN) are easy-to-deploy, low cost solutions for providing networking and internet services in environments with no network infrastructure, e.g., disaster areas and battlefields. Since electric power is not readily available in such environments battery-powered mesh routers, operating in an energy efficient manner, are required. To the best of our knowledge, the impact of energy efficient solutions, e.g., involving duty-cycling, on WMN intrusion detection systems, which require continuous monitoring, remains an open research problem. In this paper we propose that carefully chosen monitoring mesh nodes ensure continuous and complete detection coverage, while allowing non-monitoring mesh nodes to save energy through duty-cycling. We formulate the monitoring node selection problem as an optimization problem and propose distributed and centralized solutions for it, with different tradeoffs. Through extensive simulations and a proof-of-concept hardware/software implementation we demonstrate that our solutions extend the WMN lifetime by 8%, while ensuring, at the minimum, a 97% intrusion detection rate.

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.

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.

Messaging Attacks on Android: Vulnerabilities and Intrusion Detection

Directory of Open Access Journals (Sweden)

Khodor Hamandi

2015-01-01

Full Text Available Currently, Android is the leading mobile operating system in number of users worldwide. On the security side, Android has had significant challenges despite the efforts of the Android designers to provide a secure environment for apps. In this paper, we present numerous attacks targeting the messaging framework of the Android system. Our focus is on SMS, USSD, and the evolution of their associated security in Android and accordingly the development of related attacks. Also, we shed light on the Android elements that are responsible for these attacks. Furthermore, we present the architecture of an intrusion detection system (IDS that promises to thwart SMS messaging attacks. Our IDS shows a detection rate of 87.50% with zero false positives.

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

Energy Efficient Monitoring for Intrusion Detection in Battery-Powered Wireless Mesh Networks

KAUST Repository

Hassanzadeh, Amin; Stoleru, Radu; Shihada, Basem

2011-01-01

in such environments battery-powered mesh routers, operating in an energy efficient manner, are required. To the best of our knowledge, the impact of energy efficient solutions, e.g., involving duty-cycling, on WMN intrusion detection systems, which require continuous

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 System Using Deep Neural Network for In-Vehicle Network Security.

Directory of Open Access Journals (Sweden)

Min-Joo Kang

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

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

Science.gov (United States)

Kang, Min-Joo; Kang, Je-Won

2016-01-01

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

Long-distance fiber optic sensing solutions for pipeline leakage, intrusion, and ground movement detection

Science.gov (United States)

Nikles, Marc

2009-05-01

An increasing number of pipelines are constructed in remote regions affected by harsh environmental conditions where pipeline routes often cross mountain areas which are characterized by unstable grounds and where soil texture changes between winter and summer increase the probability of hazards. Third party intentional interference or accidental intrusions are a major cause of pipeline failures leading to large leaks or even explosions. Due to the long distances to be monitored and the linear nature of pipelines, distributed fiber optic sensing techniques offer significant advantages and the capability to detect and localize pipeline disturbance with great precision. Furthermore pipeline owner/operators lay fiber optic cable parallel to transmission pipelines for telecommunication purposes and at minimum additional cost monitoring capabilities can be added to the communication system. The Brillouin-based Omnisens DITEST monitoring system has been used in several long distance pipeline projects. The technique is capable of measuring strain and temperature over 100's kilometers with meter spatial resolution. Dedicated fiber optic cables have been developed for continuous strain and temperature monitoring and their deployment along the pipeline has enabled permanent and continuous pipeline ground movement, intrusion and leak detection. This paper presents a description of the fiber optic Brillouin-based DITEST sensing technique, its measurement performance and limits, while addressing future perspectives for pipeline monitoring. The description is supported by case studies and illustrated by field data.

Reduction of Motion Artifacts and Improvement of R Peak Detecting Accuracy Using Adjacent Non-Intrusive ECG Sensors

Directory of Open Access Journals (Sweden)

Minho Choi

2016-05-01

Full Text Available Non-intrusive electrocardiogram (ECG monitoring has many advantages: easy to measure and apply in daily life. However, motion noise in the measured signal is the major problem of non-intrusive measurement. This paper proposes a method to reduce the noise and to detect the R peaks of ECG in a stable manner in a sitting arrangement using non-intrusive sensors. The method utilizes two capacitive ECG sensors (cECGs to measure ECG, and another two cECGs located adjacent to the sensors for ECG are added to obtain the information on motion. Then, active noise cancellation technique and the motion information are used to reduce motion noise. To verify the proposed method, ECG was measured indoors and during driving, and the accuracy of the detected R peaks was compared. After applying the method, the sum of sensitivity and positive predictivity increased 8.39% on average and 26.26% maximally in the data. Based on the results, it was confirmed that the motion noise was reduced and that more reliable R peak positions could be obtained by the proposed method. The robustness of the new ECG measurement method will elicit benefits to various health care systems that require noninvasive heart rate or heart rate variability measurements.

Applying long short-term memory recurrent neural networks to intrusion detection

Directory of Open Access Journals (Sweden)

Ralf C. Staudemeyer

2015-07-01

Full Text Available We claim that modelling network traffic as a time series with a supervised learning approach, using known genuine and malicious behaviour, improves intrusion detection. To substantiate this, we trained long short-term memory (LSTM recurrent neural networks with the training data provided by the DARPA / KDD Cup ’99 challenge. To identify suitable LSTM-RNN network parameters and structure we experimented with various network topologies. We found networks with four memory blocks containing two cells each offer a good compromise between computational cost and detection performance. We applied forget gates and shortcut connections respectively. A learning rate of 0.1 and up to 1,000 epochs showed good results. We tested the performance on all features and on extracted minimal feature sets respectively. We evaluated different feature sets for the detection of all attacks within one network and also to train networks specialised on individual attack classes. Our results show that the LSTM classifier provides superior performance in comparison to results previously published results of strong static classifiers. With 93.82% accuracy and 22.13 cost, LSTM outperforms the winning entries of the KDD Cup ’99 challenge by far. This is due to the fact that LSTM learns to look back in time and correlate consecutive connection records. For the first time ever, we have demonstrated the usefulness of LSTM networks to intrusion detection.

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

A wireless ad hoc sensor network is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. The nodes are severely resource-constrained, with limited processing, memory and power capacities and must operate cooperatively to fulfill a common mission in typically unattended modes. In a wireless sensor network (WSN), each sensor at a node can observe locally some underlying physical phenomenon and sends a quantized version of the observation to sink (destination) nodes via wireless links. Since the wireless medium can be easily eavesdropped, links can be compromised by intrusion attacks from nodes that may mount denial-of-service attacks or insert spurious information into routing packets, leading to routing loops, long timeouts, impersonation, and node exhaustion. A cross-layer design based on protocol-layer interactions is proposed for detection and identification of various intrusion attacks on WSN operation. A feature set is formed from selected cross-layer parameters of the WSN protocol to detect and identify security threats due to intrusion attacks. A separate protocol is not constructed from the cross-layer design; instead, security attributes and quantified trust levels at and among nodes established during data exchanges complement customary WSN metrics of energy usage, reliability, route availability, and end-to-end quality-of-service (QoS) provisioning. Statistical pattern recognition algorithms are applied that use observed feature-set patterns observed during network operations, viewed as security audit logs. These algorithms provide the "best" network global performance in the presence of various intrusion attacks. A set of mobile (software) agents distributed at the nodes implement the algorithms, by moving among the layers involved in the network response at each active node

Towards Effective Network Intrusion Detection: A Hybrid Model Integrating Gini Index and GBDT with PSO

Directory of Open Access Journals (Sweden)

Longjie Li

2018-01-01

Full Text Available In order to protect computing systems from malicious attacks, network intrusion detection systems have become an important part in the security infrastructure. Recently, hybrid models that integrating several machine learning techniques have captured more attention of researchers. In this paper, a novel hybrid model was proposed with the purpose of detecting network intrusion effectively. In the proposed model, Gini index is used to select the optimal subset of features, the gradient boosted decision tree (GBDT algorithm is adopted to detect network attacks, and the particle swarm optimization (PSO algorithm is utilized to optimize the parameters of GBDT. The performance of the proposed model is experimentally evaluated in terms of accuracy, detection rate, precision, F1-score, and false alarm rate using the NSL-KDD dataset. Experimental results show that the proposed model is superior to the compared methods.

Intrusion detection model using fusion of chi-square feature selection and multi class SVM

Directory of Open Access Journals (Sweden)

Ikram Sumaiya Thaseen

2017-10-01

Full Text Available Intrusion detection is a promising area of research in the domain of security with the rapid development of internet in everyday life. Many intrusion detection systems (IDS employ a sole classifier algorithm for classifying network traffic as normal or abnormal. Due to the large amount of data, these sole classifier models fail to achieve a high attack detection rate with reduced false alarm rate. However by applying dimensionality reduction, data can be efficiently reduced to an optimal set of attributes without loss of information and then classified accurately using a multi class modeling technique for identifying the different network attacks. In this paper, we propose an intrusion detection model using chi-square feature selection and multi class support vector machine (SVM. A parameter tuning technique is adopted for optimization of Radial Basis Function kernel parameter namely gamma represented by ‘ϒ’ and over fitting constant ‘C’. These are the two important parameters required for the SVM model. The main idea behind this model is to construct a multi class SVM which has not been adopted for IDS so far to decrease the training and testing time and increase the individual classification accuracy of the network attacks. The investigational results on NSL-KDD dataset which is an enhanced version of KDDCup 1999 dataset shows that our proposed approach results in a better detection rate and reduced false alarm rate. An experimentation on the computational time required for training and testing is also carried out for usage in time critical applications.

Indian program for development of technologies relevant to reliable, non-intrusive, concealed-contraband detection

International Nuclear Information System (INIS)

Auluck, S.K.H.

2007-01-01

Generating capability for reliable, non-intrusive detection of concealed-contraband, particularly, organic contraband like explosives and narcotics, has become a national priority. This capability spans a spectrum of technologies. If a technology mission addressing the needs of a highly sophisticated technology like PFNA is set up, the capabilities acquired would be adequate to meet the requirements of many other sets of technologies. This forms the background of the Indian program for development of technologies relevant to reliable, non-intrusive, concealed contraband detection. One of the central themes of the technology development programs would be modularization of the neutron source and detector technologies, so that common elements can be combined in different ways for meeting a variety of application requirements. (author)

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

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)

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.

A Machine Learning Based Intrusion Impact Analysis Scheme for Clouds

Directory of Open Access Journals (Sweden)

Junaid Arshad

2012-01-01

Full Text Available Clouds represent a major paradigm shift, inspiring the contemporary approach to computing. They present fascinating opportunities to address dynamic user requirements with the provision of on demand expandable computing infrastructures. However, Clouds introduce novel security challenges which need to be addressed to facilitate widespread adoption. This paper is focused on one such challenge - intrusion impact analysis. In particular, we highlight the significance of intrusion impact analysis for the overall security of Clouds. Additionally, we present a machine learning based scheme to address this challenge in accordance with the specific requirements of Clouds for intrusion impact analysis. We also present rigorous evaluation performed to assess the effectiveness and feasibility of the proposed method to address this challenge for Clouds. The evaluation results demonstrate high degree of effectiveness to correctly determine the impact of an intrusion along with significant reduction with respect to the intrusion response 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.

A New Generic Taxonomy on Hybrid Malware Detection Technique

OpenAIRE

Robiah, Y.; Rahayu, S. Siti; Zaki, M. Mohd; Shahrin, S.; Faizal, M. A.; Marliza, R.

2009-01-01

Malware is a type of malicious program that replicate from host machine and propagate through network. It has been considered as one type of computer attack and intrusion that can do a variety of malicious activity on a computer. This paper addresses the current trend of malware detection techniques and identifies the significant criteria in each technique to improve malware detection in Intrusion Detection System (IDS). Several existing techniques are analyzing from 48 various researches and...

An ethernet/IP security review with intrusion detection applications

International Nuclear Information System (INIS)

Laughter, S. A.; Williams, R. D.

2006-01-01

Supervisory Control and Data Acquisition (SCADA) and automation networks, used throughout utility and manufacturing applications, have their own specific set of operational and security requirements when compared to corporate networks. The modern climate of heightened national security and awareness of terrorist threats has made the security of these systems of prime concern. There is a need to understand the vulnerabilities of these systems and how to monitor and protect them. Ethernet/IP is a member of a family of protocols based on the Control and Information Protocol (CIP). Ethernet/IP allows automation systems to be utilized on and integrated with traditional TCP/IP networks, facilitating integration of these networks with corporate systems and even the Internet. A review of the CIP protocol and the additions Ethernet/IP makes to it has been done to reveal the kind of attacks made possible through the protocol. A set of rules for the SNORT Intrusion Detection software is developed based on the results of the security review. These can be used to monitor, and possibly actively protect, a SCADA or automation network that utilizes Ethernet/IP in its infrastructure. (authors)

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...

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

International Nuclear Information System (INIS)

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

1981-01-01

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

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

Influence of seawater intrusion on microbial communities in groundwater.

Science.gov (United States)

Unno, Tatsuya; Kim, Jungman; Kim, Yumi; Nguyen, Son G; Guevarra, Robin B; Kim, Gee Pyo; Lee, Ji-Hoon; Sadowsky, Michael J

2015-11-01

Groundwater is the sole source of potable water on Jeju Island in the Republic of (South) Korea. Groundwater is also used for irrigation and industrial purposes, and it is severely impacted by seawater intrusion in coastal areas. Consequently, monitoring the intrusion of seawater into groundwater on Jeju is very important for health and environmental reasons. A number of studies have used hydrological models to predict the deterioration of groundwater quality caused by seawater intrusion. However, there is conflicting evidence of intrusion due to complicated environmental influences on groundwater quality. Here we investigated the use of next generation sequencing (NGS)-based microbial community analysis as a way to monitor groundwater quality and detect seawater intrusion. Pristine groundwater, groundwater from three coastal areas, and seawater were compared. Analysis of the distribution of bacterial species clearly indicated that the high and low salinity groundwater differed significantly with respect to microbial composition. While members of the family Parvularculaceae were only identified in high salinity water samples, a greater percentage of the phylum Actinobacteria was predominantly observed in pristine groundwater. In addition, we identified 48 shared operational taxonomic units (OTUs) with seawater, among which the high salinity groundwater sample shared a greater number of bacterial species with seawater (6.7%). In contrast, other groundwater samples shared less than 0.5%. Our results suggest that NGS-based microbial community analysis of groundwater may be a useful tool for monitoring groundwater quality and detect seawater intrusion. This technology may also provide additional insights in understanding hydrological dynamics. Copyright © 2015 Elsevier B.V. All rights reserved.

Trojan detection model based on network behavior analysis

International Nuclear Information System (INIS)

Liu Junrong; Liu Baoxu; Wang Wenjin

2012-01-01

Based on the analysis of existing Trojan detection technology, this paper presents a Trojan detection model based on network behavior analysis. First of all, we abstract description of the Trojan network behavior, then according to certain rules to establish the characteristic behavior library, and then use the support vector machine algorithm to determine whether a Trojan invasion. Finally, through the intrusion detection experiments, shows that this model can effectively detect Trojans. (authors)

A survey of intrusion detection techniques in Cloud

OpenAIRE

Modi, C.; Patel, D.; Patel, H.; Borisaniya, B.; Patel, A.; Rajarajan, M.

2013-01-01

Cloud computing provides scalable, virtualized on-demand services to the end users with greater flexibility and lesser infrastructural investment. These services are provided over the Internet using known networking protocols, standards and formats under the supervision of different managements. Existing bugs and vulnerabilities in underlying technologies and legacy protocols tend to open doors for intrusion. This paper, surveys different intrusions affecting availability, confidentiality and...

A Novel Architecture for Intrusion Detection in Mobile Ad hoc Network

OpenAIRE

Atul Patel; Ruchi Kansara; Dr. Paresh Virparia

2011-01-01

Today’s wireless networks are vulnerable in many ways including illegal use, unauthorized access, denial of service attacks, eavesdropping so called war chalking. These problems are one of the main issues for wider uses of wireless network. On wired network intruder can access by wire but in wireless it has possibilities to access the computer anywhere in neighborhood. However, securing MANETs is highly challenging issue due to their inherent characteristics. Intrusion detection is an importa...

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.

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.

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%.

The Torres del Paine intrusion as a model for a shallow magma chamber

Science.gov (United States)

Baumgartner, Lukas; Bodner, Robert; Leuthold, Julien; Muntener, Othmar; Putlitz, Benita; Vennemann, Torsten

2014-05-01

The shallow magmatic Torres del Paine Intrusive Complex (TPIC) belongs to a series of sub-volcanic and plutonic igneous bodies in Southern Chile and Argentina. This trench-parallel belt is located in a transitional position between the Patagonia Batholith in the West, and the alkaline Cenozoic plateau lavas in the East. While volumetrically small amounts of magmatism started around 28 my ago in the Torres del Paine area, and a second period occurred between 17-16 Ma, it peaked with the TPIC 12.59-12.43 Ma ago. The spectacular cliffs of the Torres del Paine National park provide a unique opportunity to study the evolution of a very shallow magma chamber and the interaction with its host rocks. Intrusion depth can be estimated based on contact metamorphic assemblages and granite solidus thermobarometry to 750±250 bars, corresponding to an intrusion depth of ca. 3km, ca. 500m above the base of the intrusion. Hornblende thermobarometry in mafic rocks agrees well with these estimates (Leuthold et al., 2014). The TPIC is composed of a granitic laccolith emplaced over 90ka (Michel et al., 2008) in 3 major, several 100m thick sheets, forming an overall thickness of nearly 2 km. Contacts are sharp between sheets, with the oldest sheet on the top and the youngest on the bottom (Michel et al., 2008). The granitic laccolith is under-plated by a ca. 400m thick mafic laccolith, built up over ca. 50ka (Leuthold et al. 2012), constructed from the bottom up. Granitic and mafic sheets are themselves composed of multiple metric to decametric pulses, mostly with ductile contacts between them, resulting in outcrop patterns resembling braided stream sediments. The contact of the TPIC with the Cretaceous flysch sediments document intrusion mechanism. Pre-existing sub-horizontal fold axes are rotated in the roof of the TPIC, clearly demonstrating ballooning of the roof; no ballooning was observed in the footwall of the intrusion. Extension during ballooning of the roof is indicated by

Intrusion detection on oil pipeline right of way using monogenic signal representation

Science.gov (United States)

Nair, Binu M.; Santhaseelan, Varun; Cui, Chen; Asari, Vijayan K.

2013-05-01

We present an object detection algorithm to automatically detect and identify possible intrusions such as construction vehicles and equipment on the regions designated as the pipeline right-of-way (ROW) from high resolution aerial imagery. The pipeline industry has buried millions of miles of oil pipelines throughout the country and these regions are under constant threat of unauthorized construction activities. We propose a multi-stage framework which uses a pyramidal template matching scheme in the local phase domain by taking a single high resolution training image to classify a construction vehicle. The proposed detection algorithm makes use of the monogenic signal representation to extract the local phase information. Computing the monogenic signal from a two dimensional object region enables us to separate out the local phase information (structural details) from the local energy (contrast) thereby achieving illumination invariance. The first stage involves the local phase based template matching using only a single high resolution training image in a local region at multiple scales. Then, using the local phase histogram matching, the orientation of the detected region is determined and a voting scheme gives a certain weightage to the resulting clusters. The final stage involves the selection of clusters based on the number of votes attained and using the histogram of oriented phase feature descriptor, the object is located at the correct orientation and scale. The algorithm is successfully tested on four different datasets containing imagery with varying image resolution and object orientation.

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.

Mineralogy and geochemistry of Skarn Fe orebody and syenodioritic intrusive host rock in Zeber Kuh prospect area (SW Bardaskan, South Khorasan province

Directory of Open Access Journals (Sweden)

Hossein Narooie

2017-11-01

Full Text Available The Zeber Kuh prospect area is located southwest of Bardaskan, South Khorasan province, in the northeastern Iran. Lithologically, the area includes Rizu and Soltanieh Formations metamorphosed carbonate rocks, which were intruded by syenogranitic and syenodioritic intrusions. Field observations and laboratory studies such as structural controls of orebody, metasomatic replacement and formation of low temperature H2O-bearing minerals, and the occurrence of magnetite and pyrite associated with chlorite, epidote, calcite, and quartz indicate that  the iron mineralization is low temperature skarn-type. The source of Fe mineralization is probably a younger intrusive rock at depth. Hydrothermal ore fluid was ascended within fault zone and/or contact between the intrusive rock and the  carbonate unit and generated orebody. Iron grade ranges from 54 to 65 wt.% and sulfur value is > 3 wt.%. Magnetite chemistry and Ti, V, Al, Mn, Ni, and Cr contents are similar to skarn deposit. Biotite syenodiorite host rock has hypidiomorphic granular texture and it consists of plagioclase, K-feldspar, biotite, and apatite minerals. Chemically, this intrusive rock is K-series alkaline type, which was generated in within plate zone. This magma is characterized by strong enrichment in LREE, LILE (Rb, Cs, Ba, and K, HFSE (Nb, Zr, and Ti, and P elements. The primary magma is produced by low degree partial melting of garnet lherzolite from asthenospheric to boundary of asthenospheric-lithospheric mantle.

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.

Network Anomaly Detection Based on Wavelet Analysis

Directory of Open Access Journals (Sweden)

Ali A. Ghorbani

2008-11-01

Full Text Available Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

Network Anomaly Detection Based on Wavelet Analysis

Science.gov (United States)

Lu, Wei; Ghorbani, Ali A.

2008-12-01

Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

Non-intrusive, fast and sensitive ammonia detection by laser photothermal deflection

International Nuclear Information System (INIS)

Vries, H.S.M. de; Harren, F.J.M.; Wyers, G.P.; Otjes, R.P.; Slanina, J.; Reuss, J.

1995-01-01

A recently developed non-intrusive photothermal deflection (PTD) instrument allows sensitive, rapid and quantitative detection of local ammonia concentrations in the air. Ammonia is vibrationally excited by an infrared CO 2 laser in an intracavity configuration. A HeNe beam passing over the CO 2 laser beam (multipass arrangement) is deflected by the induced refractive index gradient. The detection limit for ammonia in ambient air is 0.5 ppbv with a spatial resolution of a few mm 3 . The time resolution is 0.1 s (single line) or 15 s (multi line). The system is fully automated and suited for non-stop measuring periods of at least one week. Results were compared to those obtained with a continuous-flow denuder (CFD). (author)

Constructing APT Attack Scenarios Based on Intrusion Kill Chain and Fuzzy Clustering

Directory of Open Access Journals (Sweden)

Ru Zhang

2017-01-01

Full Text Available The APT attack on the Internet is becoming more serious, and most of intrusion detection systems can only generate alarms to some steps of APT attack and cannot identify the pattern of the APT attack. To detect APT attack, many researchers established attack models and then correlated IDS logs with the attack models. However, the accuracy of detection deeply relied on the integrity of models. In this paper, we propose a new method to construct APT attack scenarios by mining IDS security logs. These APT attack scenarios can be further used for the APT detection. First, we classify all the attack events by purpose of phase of the intrusion kill chain. Then we add the attack event dimension to fuzzy clustering, correlate IDS alarm logs with fuzzy clustering, and generate the attack sequence set. Next, we delete the bug attack sequences to clean the set. Finally, we use the nonaftereffect property of probability transfer matrix to construct attack scenarios by mining the attack sequence set. Experiments show that the proposed method can construct the APT attack scenarios by mining IDS alarm logs, and the constructed scenarios match the actual situation so that they can be used for APT attack detection.

A new detection method based on CFAR and DE for OFPS

Science.gov (United States)

Qiu, Zezheng; Zheng, Tong; Qu, Hongquan; Pang, Liping

2016-09-01

Optical fiber pre-warning system (OFPS) is widely utilized in pipeline transport fields. The intrusions of OFPS need to be located. In this system, the original signals consist of noises, interferences, and intrusion signals. Here, noises are background and harmless interferences possessing with high power, and the intrusion signals are the main target of detection in this system. Hence, the study stresses on extracting the intrusion signals from the total ones. The proposed method can be divided into two parts, constant false alarm rate (CFAR) and dilation and erosion (DE). The former is applied to eliminate noises, and the latter is to remove interferences. According to some researches, the feature of noise background accords with the CFAR spatial detection. Furthermore, the detection results after CFAR can be presented as a binary image of time and space. Besides, interferences are relatively disconnected. Consequently, they can be eliminated by DE which is introduced from the image processing. To sum up, this novel method is based on CFAR and DE which can eliminate noises and interferences effectively. Moreover, it performs a brilliant detection performance. A series of tests were developed in Men Tou Gou of Beijing, China, and the reliability of proposed method can be verified by these tests.

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.

Preliminary experimental results for a non-intrusive scheme for the detection of flaws in metal pipelines

Science.gov (United States)

Aydin, K.; Shinde, S.; Suhail, M.; Vyas, A.; Zieher, K. W.

2002-05-01

An acoustic pulse echo scheme for non-intrusive detection of flaws in metal pipelines has been investigated in the laboratory. The primary pulse is generated by a pulsed magnetic field enclosing a short section of a free pipe. The detection is by an electrostatic detector surrounding a short section of the pipe. Reflected pulses from thin areas, with a longitudinal extension of about one pipe radius and a reduction of the wall thickness of 40%, can be detected clearly.

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 Network Intrusion Detection Methods

Directory of Open Access Journals (Sweden)

Pavel Nevlud

2013-01-01

Full Text Available The article deals with detection of network anomalies. Network anomalies include everything that is quite different from the normal operation. For detection of anomalies were used machine learning systems. Machine learning can be considered as a support or a limited type of artificial intelligence. A machine learning system usually starts with some knowledge and a corresponding knowledge organization so that it can interpret, analyse, and test the knowledge acquired. There are several machine learning techniques available. We tested Decision tree learning and Bayesian networks. The open source data-mining framework WEKA was the tool we used for testing the classify, cluster, association algorithms and for visualization of our results. The WEKA is a collection of machine learning algorithms for data mining tasks.

Community-Based Intrusion Detection

OpenAIRE

Weigert, Stefan

2017-01-01

Today, virtually every company world-wide is connected to the Internet. This wide-spread connectivity has given rise to sophisticated, targeted, Internet-based attacks. For example, between 2012 and 2013 security researchers counted an average of about 74 targeted attacks per day. These attacks are motivated by economical, financial, or political interests and commonly referred to as “Advanced Persistent Threat (APT)” attacks. Unfortunately, many of these attacks are successful and the advers...

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...

Subsurface event detection and classification using Wireless Signal Networks.

Science.gov (United States)

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

2012-11-05

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

The NIDS Cluster: Scalable, Stateful Network Intrusion Detection on Commodity Hardware

Energy Technology Data Exchange (ETDEWEB)

Tierney, Brian L; Vallentin, Matthias; Sommer, Robin; Lee, Jason; Leres, Craig; Paxson, Vern; Tierney, Brian

2007-09-19

In this work we present a NIDS cluster as a scalable solution for realizing high-performance, stateful network intrusion detection on commodity hardware. The design addresses three challenges: (i) distributing traffic evenly across an extensible set of analysis nodes in a fashion that minimizes the communication required for coordination, (ii) adapting the NIDS's operation to support coordinating its low-level analysis rather than just aggregating alerts; and (iii) validating that the cluster produces sound results. Prototypes of our NIDS cluster now operate at the Lawrence Berkeley National Laboratory and the University of California at Berkeley. In both environments the clusters greatly enhance the power of the network security monitoring.

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...

Time-resolved seismic tomography detects magma intrusions at Mount Etna.

Science.gov (United States)

Patanè, D; Barberi, G; Cocina, O; De Gori, P; Chiarabba, C

2006-08-11

The continuous volcanic and seismic activity at Mount Etna makes this volcano an important laboratory for seismological and geophysical studies. We used repeated three-dimensional tomography to detect variations in elastic parameters during different volcanic cycles, before and during the October 2002-January 2003 flank eruption. Well-defined anomalous low P- to S-wave velocity ratio volumes were revealed. Absent during the pre-eruptive period, the anomalies trace the intrusion of volatile-rich (>/=4 weight percent) basaltic magma, most of which rose up only a few months before the onset of eruption. The observed time changes of velocity anomalies suggest that four-dimensional tomography provides a basis for more efficient volcano monitoring and short- and midterm eruption forecasting of explosive activity.

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

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– ...

An Entropy-Based Network Anomaly Detection Method

Directory of Open Access Journals (Sweden)

Przemysław Bereziński

2015-04-01

Full Text Available Data mining is an interdisciplinary subfield of computer science involving methods at the intersection of artificial intelligence, machine learning and statistics. One of the data mining tasks is anomaly detection which is the analysis of large quantities of data to identify items, events or observations which do not conform to an expected pattern. Anomaly detection is applicable in a variety of domains, e.g., fraud detection, fault detection, system health monitoring but this article focuses on application of anomaly detection in the field of network intrusion detection.The main goal of the article is to prove that an entropy-based approach is suitable to detect modern botnet-like malware based on anomalous patterns in network. This aim is achieved by realization of the following points: (i preparation of a concept of original entropy-based network anomaly detection method, (ii implementation of the method, (iii preparation of original dataset, (iv evaluation of the method.

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.

Identifying Likely Disk-hosting M dwarfs with Disk Detective

Science.gov (United States)

Silverberg, Steven; Wisniewski, John; Kuchner, Marc J.; Disk Detective Collaboration

2018-01-01

M dwarfs are critical targets for exoplanet searches. Debris disks often provide key information as to the formation and evolution of planetary systems around higher-mass stars, alongside the planet themselves. However, less than 300 M dwarf debris disks are known, despite M dwarfs making up 70% of the local neighborhood. The Disk Detective citizen science project has identified over 6000 new potential disk host stars from the AllWISE catalog over the past three years. Here, we present preliminary results of our search for new disk-hosting M dwarfs in the survey. Based on near-infrared color cuts and fitting stellar models to photometry, we have identified over 500 potential new M dwarf disk hosts, nearly doubling the known number of such systems. In this talk, we present our methodology, and outline our ongoing work to confirm systems as M dwarf disks.

Non-Intrusive Intelligibility Prediction Using a Codebook-Based Approach

DEFF Research Database (Denmark)

Sørensen, Charlotte; Kavalekalam, Mathew Shaji; Xenaki, Angeliki

2017-01-01

It could be beneficial for users of hearing aids if these were able to automatically adjust the processing according to the speech intelligibility in the specific acoustic environment. Most speech intelligibility metrics are intrusive, i.e., they require a clean reference signal, which is rarely...... a high correlation between the proposed non-intrusive codebookbased STOI (NIC-STOI) and the intrusive STOI indicating that NIC-STOI is a suitable metric for automatic classification of speech signals...

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

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 study on efficient detection of network-based IP spoofing DDoS and malware-infected Systems.

Science.gov (United States)

Seo, Jung Woo; Lee, Sang Jin

2016-01-01

Large-scale network environments require effective detection and response methods against DDoS attacks. Depending on the advancement of IT infrastructure such as the server or network equipment, DDoS attack traffic arising from a few malware-infected systems capable of crippling the organization's internal network has become a significant threat. This study calculates the frequency of network-based packet attributes and analyzes the anomalies of the attributes in order to detect IP-spoofed DDoS attacks. Also, a method is proposed for the effective detection of malware infection systems triggering IP-spoofed DDoS attacks on an edge network. Detection accuracy and performance of the collected real-time traffic on a core network is analyzed thru the use of the proposed algorithm, and a prototype was developed to evaluate the performance of the algorithm. As a result, DDoS attacks on the internal network were detected in real-time and whether or not IP addresses were spoofed was confirmed. Detecting hosts infected by malware in real-time allowed the execution of intrusion responses before stoppage of the internal network caused by large-scale attack traffic.

Reactive and multiphase modelling for the identification of monitoring parameters to detect CO2 intrusion into freshwater aquifers

Science.gov (United States)

Fahrner, S.; Schaefer, D.; Wiegers, C.; Köber, R.; Dahmke, A.

2011-12-01

A monitoring at geological CO2 storage sites has to meet environmental, regulative, financial and public demands and thus has to enable the detection of CO2 leakages. Current monitoring concepts for the detection of CO2 intrusion into freshwater aquifers located above saline storage formations in course of leakage events lack the identification of monitoring parameters. Their response to CO2 intrusion still has to be enlightened. Scenario simulations of CO2 intrusion in virtual synthetic aquifers are performed using the simulators PhreeqC and TOUGH2 to reveal relevant CO2-water-mineral interactions and multiphase behaviour on potential monitoring parameters. The focus is set on pH, total dissolved inorganic carbon (TIC) and the hydroelectric conductivity (EC). The study aims at identifying at which conditions the parameters react rapidly, durable and in a measurable degree. The depth of the aquifer, the mineralogy, the intrusion rates, the sorption specification and capacities, and groundwater flow velocities are varied in the course of the scenario modelling. All three parameters have been found suited in most scenarios. However, in case of a lack of calcite combined with low saturation of the water with respect to CO2 and shallow conditions, changes are close to the measurement resolution. Predicted changes in EC result from the interplay between carbonic acid production and its dissociation, and pH buffering by mineral dissolution. The formation of a discrete gas phase in cases of full saturation of the groundwater in confined aquifers illustrates the potential bipartite resistivity response: An increased hydroelectric conductivity at locations with dissolved CO2, and a high resistivity where the gas phase dominates the pore volume occupation. Increased hydrostatic pressure with depth and enhanced groundwater flow velocities enforce gas dissolution and diminish the formation of a discrete gas phase. Based on the results, a monitoring strategy is proposed which

Formation of thick stratiform Fe-Ti oxide layers in layered intrusion and frequent replenishment of fractionated mafic magma: Evidence from the Panzhihua intrusion, SW China

Science.gov (United States)

Song, Xie-Yan; Qi, Hua-Wen; Hu, Rui-Zhong; Chen, Lie-Meng; Yu, Song-Yue; Zhang, Jia-Fei

2013-03-01

Panzhihua intrusion is one of the largest layered intrusions that hosts huge stratiform Fe-Ti oxide layers in the central part of the Emeishan large igneous province, SW China. Up to 60 m thick stratiform massive Fe-Ti oxide layers containing 85 modal% of magnetite and ilmenite and overlying magnetite gabbro compose cyclic units of the Lower Zone of the intrusion. The cyclic units of the Middle Zone consist of magnetite gabbro and overlying gabbro. In these cyclic units, contents of Fe2O3(t), TiO2 and Cr and Fe3+/Ti4+ ratio of the rocks decrease upward, Cr content of magnetite and forsterite percentage of olivine decrease as well. The Upper Zone consists of apatite gabbro characterized by enrichment of incompatible elements (e.g., 12-18 ppm La, 20-28 ppm Y) and increasing of Fe3+/Ti4+ ratio (from 1.3 to 2.3) upward. These features indicate that the Panzhihua intrusion was repeatedly recharged by more primitive magma and evolved magmas had been extracted. Calculations using MELTS indicate that extensive fractionation of olivine and clinopyroxene in deep level resulted in increasing Fe and Ti contents in the magma. When these Fe-Ti-enriched magmas were emplaced along the base of the Panzhihua intrusion, Fe-Ti oxides became an early crystallization phase, leading to a residual magma of lower density. We propose that the unusually thick stratiform Fe-Ti oxide layers resulted from coupling of gravity settling and sorting of the crystallized Fe-Ti oxides from Fe-Ti-enriched magmas and frequent magma replenishment along the floor of the magma chamber.

Subsurface Event Detection and Classification Using Wireless Signal Networks

Directory of Open Access Journals (Sweden)

Muhannad T. Suleiman

2012-11-01

Full Text Available Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs. The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

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). ...

Probabilistic monitoring in intrusion detection module for energy efficiency in mobile ad hoc networks

Science.gov (United States)

De Rango, Floriano; Lupia, Andrea

2016-05-01

MANETs allow mobile nodes communicating to each other using the wireless medium. A key aspect of these kind of networks is the security, because their setup is done without an infrastructure, so external nodes could interfere in the communication. Mobile nodes could be compromised, misbehaving during the multi-hop transmission of data, or they could have a selfish behavior to save energy, which is another important constraint in MANETs. The detection of these behaviors need a framework that takes into account the latest interactions among nodes, so malicious or selfish nodes could be detected also if their behavior is changed over time. The monitoring activity increases the energy consumption, so our proposal takes into account this issue reducing the energy required by the monitoring system, keeping the effectiveness of the intrusion detection system. The results show an improvement in the saved energy, improving the detection performance too.

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

The assessment of human intrusion into underground repositories for radioactive waste Volume 2: Appendices

International Nuclear Information System (INIS)

Nancarrow, D.J.; Little, R.H.; Ashton, J.; Staunton, G.M.

1990-01-01

This report has been prepared with the primary objective of establishing a methodology for the assessment of human intrusion into deep underground repositories for radioactive wastes. The disposal concepts considered are those studied in the performance assessment studies Pagis and Pacoma, coordinated by the CEC. These comprise four types of host rock, namely: clay, granite, salt and the sub-seabed. Following a review of previous assessments of human intrusion, a list of relevant human activities is derived. This forms the basis for detailed characterization of groundwater abstraction and of exploitation of mineral and other resources. Approaches to assessment of intrusion are reviewed and consideration is given to the estimation of probabilities for specific types of intrusion events. Calculational schemes are derived for specific intrusion events and dosimetric factors are presented. A review is also presented of the capacity for reduction of the risks associated with intrusions. Finally, conclusions from the study are presented

Improving SCADA security of a local process with a power grid model

NARCIS (Netherlands)

Chromik, Justyna Joanna; Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.

Security of networks controlling smart grids is an important subject. The shift of the power grid towards a smart grid results in more distributed control functions, while intrusion detection of the control network mostly remains centrally based. Moreover, existing local (host-based) intrusion

The assessment of human intrusion into underground repositories for radioactive waste Volume 1: Main report

International Nuclear Information System (INIS)

Nancarrow, D.J.; Little, R.H.; Asthon, J.; Staunton, G.M.

1990-01-01

This report has been prepared with the primary objective of establishing a methodology for the assessment of human intrusion into deep underground repositories for radioactive wastes. The disposal concepts considered are those studied in the performance assessment studies Pagis and Pacoma, coordinated by the CEC. These comprise four types of host rock, namely: clay, granite, salt and the sub-seabed. Following a review of previous assessments of human intrusion, a list of relevant human activities is derived. This forms the basis for detailed characterization of groundwater abstraction and of exploitation of mineral and other resources. Approaches to assessment of intrusion are reviewed and consideration is given to the estimation of probabilities for specific types of intrusion events. Calculational schemes are derived for specific intrusion events and dosimetric factors are presented. A review is also presented of the capacity for reduction of the risks associated with intrusions. Finally, conclusions from the study are presented

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.

Influence of crystallised igneous intrusions on fault nucleation and reactivation during continental extension

Science.gov (United States)

Magee, Craig; McDermott, Kenneth G.; Stevenson, Carl T. E.; Jackson, Christopher A.-L.

2014-05-01

Continental rifting is commonly accommodated by the nucleation of normal faults, slip on pre-existing fault surfaces and/or magmatic intrusion. Because crystallised igneous intrusions are pervasive in many rift basins and are commonly more competent (i.e. higher shear strengths and Young's moduli) than the host rock, it is theoretically plausible that they locally intersect and modify the mechanical properties of pre-existing normal faults. We illustrate the influence that crystallised igneous intrusions may have on fault reactivation using a conceptual model and observations from field and subsurface datasets. Our results show that igneous rocks may initially resist failure, and promote the preferential reactivation of favourably-oriented, pre-existing faults that are not spatially-associated with solidified intrusions. Fault segments situated along strike from laterally restricted fault-intrusion intersections may similarly be reactivated. This spatial and temporal control on strain distribution may generate: (1) supra-intrusion folds in the hanging wall; (2) new dip-slip faults adjacent to the igneous body; or (3) sub-vertical, oblique-slip faults oriented parallel to the extension direction. Importantly, stress accumulation within igneous intrusions may eventually initiate failure and further localise strain. The results of our study have important implications for the structural of sedimentary basins and the subsurface migration of hydrocarbons and mineral-bearing fluids.

Intrusion Prevention and Detection in Grid Computing - The ALICE Case

CERN Document Server

INSPIRE-00416173; Kebschull, Udo

2015-01-01

Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is used in the ALICE experiment at European Organization for Nuclear Research CERN. Physicists can submit jobs used to process the huge amount of particle collision data produced by the Large Hadron Collider (LHC). Grids face complex security challenges. They are interesting targets for attackers seeking for huge computational resources. Since users can execute arbitrary code in the worker nodes on the Grid sites, special care should be put in this environment. Automatic tools to harden and monitor this scenario are required. Currently, there is no integrated solution for such requirement. This paper describes a new security framework to allow execution of job payloads in a sandboxed context. It also allows process behavior monitoring to detect intrusions, even when new attack methods or zero day vulnerabilities are exploited, by a Machin...

A Nuisance Alarm Data System for evaluation of intrusion detectors

International Nuclear Information System (INIS)

Ream, W.K.

1990-01-01

A Nuisance Alarm Data System (NADS) was developed to gather long-term background alarm data on exterior intrusion detectors as part of their evaluation. Since nuisance alarms play an important part in the selection of intrusion detectors for use at Department of Energy (DOE) facilities, an economical and reliable way to monitor and record these alarms was needed. NADS consists of an IBM personal computer and printer along with other commercial units to communicate with the detectors, to gather weather data, and to record video for assessment. Each alarm, its assessment, and the weather conditions occurring at alarm time are placed into a data base that is used in the evaluation of the detector. The operating software is written in Turbo Pascal for easy maintenance and modification. A portable system, based on the NADS design, has been built and shipped to other DOE locations to do on-site alarm monitoring. This has been valuable for the comparison of different detectors in the on-site environment and for testing new detectors when the appropriate conditions do not exist or cannot be simulated at the Exterior Intrusion Detection Testbed

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

OpenAIRE

CHITEA, Florina; GEORGESCU, Paul; IOANE, Dumitru

2011-01-01

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

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.

A comparative performance evaluation of intrusion detection techniques for hierarchical wireless sensor networks

Directory of Open Access Journals (Sweden)

H.H. Soliman

2012-11-01

Full Text Available An explosive growth in the field of wireless sensor networks (WSNs has been achieved in the past few years. Due to its important wide range of applications especially military applications, environments monitoring, health care application, home automation, etc., they are exposed to security threats. Intrusion detection system (IDS is one of the major and efficient defensive methods against attacks in WSN. Therefore, developing IDS for WSN have attracted much attention recently and thus, there are many publications proposing new IDS techniques or enhancement to the existing ones. This paper evaluates and compares the most prominent anomaly-based IDS systems for hierarchical WSNs and identifying their strengths and weaknesses. For each IDS, the architecture and the related functionality are briefly introduced, discussed, and compared, focusing on both the operational strengths and weakness. In addition, a comparison of the studied IDSs is carried out using a set of critical evaluation metrics that are divided into two groups; the first one related to performance and the second related to security. Finally based on the carried evaluation and comparison, a set of design principles are concluded, which have to be addressed and satisfied in future research of designing and implementing IDS for WSNs.

Efficient Network Monitoring for Attack Detection

OpenAIRE

Limmer, Tobias

2011-01-01

Techniques for network-based intrusion detection have been evolving for years, and the focus of most research is on detection algorithms, although networks are distributed and dynamically managed nowadays. A data processing framework is required that allows to embed multiple detection techniques and to provide data with the needed aggregation levels. Within that framework, this work concentrates on methods that improve the interoperability of intrusion detection techniques and focuses on data...

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.

Whole-rock and mineral compositional constraints on the magmatic evolution of the Ni-Cu-(PGE) sulfide ore-bearing Kevitsa intrusion, northern Finland

Science.gov (United States)

Luolavirta, Kirsi; Hanski, Eero; Maier, Wolfgang; Santaguida, Frank

2018-01-01

The 2.06 Ga mafic-ultramafic Kevitsa intrusion is located in the Central Lapland greenstone belt. The lower ultramafic part of the intrusion hosts a large disseminated Ni-Cu-(PGE) sulfide deposit with Ni tenors ranging widely from architecture, variations in whole-rock and mineral compositions, and the presence of numerous inclusions and xenoliths. The OLPXs are mainly composed of cumulus olivine (Fo77-89) and clinopyroxene (Mg#81-92) with variable amounts of oikocrystic orthopyroxene (Mg#79-84). They comprise the bulk of the ultramafic cumulates and are the dominant host rocks to the sulfide ore. The host rocks to the regular and false ore type are mineralogically and compositionally similar (Fo 80-83, mostly) and show mildly LREE-enriched REE patterns (CeN/YbN 2), characteristic for the bulk of the Kevitsa ultramafic cumulates. The abundance of orthopyroxene and magnetite is lowest in the host rocks to the Ni-PGE ore type, being in line with the mineral compositions of the silicates, which are the most primitive in the intrusion. However, it contrasts with the LREE-enriched nature of the ore type (CeN/YbN 7), indicating significant involvement of crustal material in the magma. The contrasting intrusive stratigraphy in the different parts of the intrusion likely reflects different emplacement histories. It is proposed that the Kevitsa magma chamber was initially filled by stable continuous flow ("single" input) of basaltic magma followed by differentiation in an at least nearly closed system. In the following stage, new magma pulses were repeatedly emplaced into the interior of the intrusion in a dynamic (open) system forming the sulfide ore bodies. To gain the peculiar compositional and mineralogical characteristics of the Ni-PGE ore type, the related magma probably interacted with different country rocks en route to the Kevitsa magma chamber.

Paleomagnetic record of a geomagnetic field reversal from late miocene mafic intrusions, southern nevada.

Science.gov (United States)

Ratcliff, C D; Geissman, J W; Perry, F V; Crowe, B M; Zeitler, P K

1994-10-21

Late Miocene (about 8.65 million years ago) mafic intrusions and lava flows along with remagnetized host rocks from Paiute Ridge, southern Nevada, provide a high-quality paleomagnetic record of a geomagnetic field reversal. These rocks yield thermoremanent magnetizations with declinations of 227 degrees to 310 degrees and inclinations of -7 degrees to 49 degrees , defining a reasonably continuous virtual geomagnetic pole path over west-central Pacific longitudes. Conductive cooling estimates for the intrusions suggest that this field transition, and mafic magmatism, lasted only a few hundred years. Because this record comes principally from intrusive rocks, rather than sediments or lavas, it is important in demonstrating the longitudinal confinement of the geomagnetic field during a reversal.

Successive reactive liquid flow episodes in a layered intrusion (Unit 9, Rum Eastern Layered Intrusion, Scotland)

Science.gov (United States)

Leuthold, Julien; Blundy, Jon; Holness, Marian

2014-05-01

moving upwards and laterally through the cumulate pile. The Rum layered intrusion is an open intrusive complex, composed of individual partially molten zones, evolving independently. The Rum layered intrusion offers a direct overview of processes taking place in shallow intra-plate and ridge magma chambers. Intrusion of hot magma into a pre-existing cumulate pile results in the modification both the incoming liquid and the host-rock cumulates. Our study highlights the necessity of considering this type of process when modelling the geochemistry of lavas erupted from magma chambers subject to repeated replenishment.

Evaluation of intrusion sensors and video assessment in areas of restricted passage

International Nuclear Information System (INIS)

Hoover, C.E.; Ringler, C.E.

1996-04-01

This report discusses an evaluation of intrusion sensors and video assessment in areas of restricted passage. The discussion focuses on applications of sensors and video assessment in suspended ceilings and air ducts. It also includes current and proposed requirements for intrusion detection and assessment. Detection and nuisance alarm characteristics of selected sensors as well as assessment capabilities of low-cost board cameras were included in the evaluation

Acoustic emission intrusion detector

International Nuclear Information System (INIS)

Carver, D.W.; Whittaker, J.W.

1980-01-01

An intrusion detector is provided for detecting a forcible entry into a secured structure while minimizing false alarms. The detector uses a piezoelectric crystal transducer to sense acoustic emissions. The transducer output is amplified by a selectable gain amplifier to control the sensitivity. The rectified output of the amplifier is applied to a Schmitt trigger circuit having a preselected threshold level to provide amplitude discrimination. Timing circuitry is provided which is activated by successive pulses from the Schmitt trigger which lie within a selected time frame for frequency discrimination. Detected signals having proper amplitude and frequency trigger an alarm within the first complete cycle time of a detected acoustical disturbance signal

Deconstructing the Assessment of Anomaly-based Intrusion Detectors for Critical Applications

Energy Technology Data Exchange (ETDEWEB)

Viswanathan, Arun; Tan, Kymie; Neuman, Clifford

2013-10-01

Anomaly detection is a key strategy for cyber intrusion detection because it is conceptually capable of detecting novel attacks. This makes it an appealing defensive technique for environments such as the nation's critical infrastructures that is currently facing increased cyber adversarial activity. When considering deployment within the purview of such critical infrastructures it is imperative that the technology is well understood and reliable, where its performance is benchmarked on the results of principled assessments. This paper works towards such an imperative by analyzing the current state of anomaly detector assessments with a view toward mission critical deployments. We compile a framework of key evaluation constructs that identify how and where current assessment methods may fall short in providing sufficient insight into detector performance characteristics. Within the context of three case studies from literature, we show how error factors that influence the performance of detectors interact with different phases of a canonical evaluation strategy to compromise the integrity of the final results.

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 ...

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

Intrusion Prevention and Detection in Grid Computing - The ALICE Case

Science.gov (United States)

Gomez, Andres; Lara, Camilo; Kebschull, Udo

2015-12-01

Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is used in the ALICE experiment at European Organization for Nuclear Research CERN. Physicists can submit jobs used to process the huge amount of particle collision data produced by the Large Hadron Collider (LHC). Grids face complex security challenges. They are interesting targets for attackers seeking for huge computational resources. Since users can execute arbitrary code in the worker nodes on the Grid sites, special care should be put in this environment. Automatic tools to harden and monitor this scenario are required. Currently, there is no integrated solution for such requirement. This paper describes a new security framework to allow execution of job payloads in a sandboxed context. It also allows process behavior monitoring to detect intrusions, even when new attack methods or zero day vulnerabilities are exploited, by a Machine Learning approach. We plan to implement the proposed framework as a software prototype that will be tested as a component of the ALICE Grid middleware.

Intrusion Prevention and Detection in Grid Computing - The ALICE Case

International Nuclear Information System (INIS)

Gomez, Andres; Lara, Camilo; Kebschull, Udo

2015-01-01

Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is used in the ALICE experiment at European Organization for Nuclear Research CERN. Physicists can submit jobs used to process the huge amount of particle collision data produced by the Large Hadron Collider (LHC). Grids face complex security challenges. They are interesting targets for attackers seeking for huge computational resources. Since users can execute arbitrary code in the worker nodes on the Grid sites, special care should be put in this environment. Automatic tools to harden and monitor this scenario are required. Currently, there is no integrated solution for such requirement. This paper describes a new security framework to allow execution of job payloads in a sandboxed context. It also allows process behavior monitoring to detect intrusions, even when new attack methods or zero day vulnerabilities are exploited, by a Machine Learning approach. We plan to implement the proposed framework as a software prototype that will be tested as a component of the ALICE Grid middleware. (paper)

Geochemistry of Hydrothermal Alteration Associated with Cenozoic Intrusion-Hosted Cu-Pb-Zn Mineralization at Tavşanlı Area, Kütahya, NW Turkey

Directory of Open Access Journals (Sweden)

Mustafa Kumral

2016-02-01

Full Text Available The Miocene magmatic intrusion in the Tavşanlı zone of the Kütahya-Bolkardağ Belt (KBB in the northwestern region of Turkey is represented by the Eğrigöz granitoids. This paper studies the petrology and geochemistry of hydrothermal alterations associated with the vein-type Cu-Pb-Zn mineralization hosted by this pluton, focusing on the determination of the mass gains and losses of chemical components, which reflect the chemical exchanges between the host rocks and hydrothermal fluids. Vein-type Cu-Pb-Zn mineralization is closely associated with intense hydrothermal alterations within the brecciation, quartz stockwork veining, and brittle fracture zones that are controlled by NW-SE trending faults cutting through the Eğrigöz granitoids. Paragenetic relationships reveal three stages of mineralization: pre-ore, ore, and supergene. The ore mineralogy typically includes hypogene chalcopyrite, sphalerite, galena, and pyrite, with locally supergene covellite, malachite, and azurite. Wall-rock hypogene hydrothermal alterations include pervasive silicification, sulfidation, sericitization, and selective carbonatization and albitization. These are distributed in three main alteration zones (zone 1: silicified/iron carbonatized alterations ± albite, zone 2: argillic-silicic alterations, and zone 3: phyllic alterations. Based on the gains and losses of mass and volume (calculated by the GEOISO-Windows™ program, zone 1 has a higher mass and volume gain than zones 2 and 3. Non-systematic zonal distributions of alterations are observed in which the silicic-carbonate alterations +/− albitization appeared in zone 1 in the center and the phyllic-argillic alterations appeared in zones 2 and 3, with an increase in base metals (Cu-Pb-Zn in the zone from Cu, Cu-Pb, to Cu-Pb-Zn moving outwards.

Detection of Intelligent Intruders in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Yun Wang

2016-01-01

Full Text Available Most of the existing research works on the intrusion detection problem in a wireless sensor network (WSN assume linear or random mobility patterns in abstracting intruders’ models in traversing the WSN field. However, in real-life WSN applications, an intruder is usually an intelligent mobile robot with environment learning and detection avoidance capability (i.e., the capability to avoid surrounding sensors. Due to this, the literature results based on the linear or random mobility models may not be applied to the real-life WSN design and deployment for efficient and effective intrusion detection in practice. This motivates us to investigate the impact of intruder’s intelligence on the intrusion detection problem in a WSN for various applications. To be specific, we propose two intrusion algorithms, the pinball and flood-fill algorithms, to mimic the intelligent motion and behaviors of a mobile intruder in detecting and circumventing nearby sensors for detection avoidance while heading for its destination. The two proposed algorithms are integrated into a WSN framework for intrusion detection analysis in various circumstances. Monte Carlo simulations are conducted, and the results indicate that: (1 the performance of a WSN drastically changes as a result of the intruder’s intelligence in avoiding sensor detections and intrusion algorithms; (2 network parameters, including node density, sensing range and communication range, play a crucial part in the effectiveness of the intruder’s intrusion algorithms; and (3 it is imperative to integrate intruder’s intelligence in the WSN research for intruder detection problems under various application circumstances.

Technical bases for leak detection surveillance of waste storage tanks. Revision 1

International Nuclear Information System (INIS)

Johnson, M.G.; Badden, J.J.

1995-01-01

This document provides the technical bases for specification limits, monitoring frequencies and baselines used for leak detection and intrusion (for single shell tanks only) in all single and double shell radioactive waste storage tanks, waste transfer lines, and most catch tanks and receiver tanks in the waste tank farms and associated areas at Hanford

Acceptance- and imagery-based strategies can reduce chocolate cravings: A test of the elaborated-intrusion theory of desire.

Science.gov (United States)

Schumacher, Sophie; Kemps, Eva; Tiggemann, Marika

2017-06-01

The elaborated-intrusion theory of desire proposes that craving is a two-stage process whereby initial intrusions about a desired target are subsequently elaborated with mental imagery. The present study tested whether the craving reduction strategies of cognitive defusion and guided imagery could differentially target the intrusion and elaboration stages, respectively, and thus differentially impact the craving process. Participants were randomly assigned to a cognitive defusion, a guided imagery or a mind-wandering control condition. Pre- and post-intervention chocolate-related thoughts, intrusiveness of thoughts, vividness of imagery, craving intensity, and chocolate consumption were compared. Experiment 1 recruited a general sample of young women (n = 94), whereas Experiment 2 recruited a sample of chocolate cravers who wanted to reduce their chocolate consumption (n = 97). Across both experiments, cognitive defusion lowered intrusiveness of thoughts, vividness of imagery and craving intensity. Guided imagery reduced chocolate-related thoughts, intrusiveness, vividness and craving intensity for chocolate cravers (Experiment 2), but not for the general sample (Experiment 1). There were no group differences in chocolate consumption in either experiment. Results add to existing evidence supporting the elaborated-intrusion theory of desire in the food domain, and suggest that acceptance- and imagery-based techniques have potential for use in combatting problematic cravings. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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...

Magmatic ore deposits in layered intrusions - Descriptive model for reef-type PGE and contact-type Cu-Ni-PGE deposits

Science.gov (United States)

Zientek, Michael L.

2012-01-01

Layered, ultramafic to mafic intrusions are uncommon in the geologic record, but host magmatic ore deposits containing most of the world's economic concentrations of platinum-group elements (PGE) (figs. 1 and 2). These deposits are mined primarily for their platinum, palladium, and rhodium contents (table 1). Magmatic ore deposits are derived from accumulations of crystals of metallic oxides, or immiscible sulfide, or oxide liquids that formed during the cooling and crystallization of magma, typically with mafic to ultramafic compositions. "PGE reefs" are stratabound PGE-enriched lode mineralization in mafic to ultramafic layered intrusions. The term "reef" is derived from Australian and South African literature for this style of mineralization and used to refer to (1) the rock layer that is mineralized and has distinctive texture or mineralogy (Naldrett, 2004), or (2) the PGE-enriched sulfide mineralization that occurs within the rock layer. For example, Viljoen (1999) broadly defined the Merensky Reef as "a mineralized zone within or closely associated with an unconformity surface in the ultramafic cumulate at the base of the Merensky Cyclic Unit." In this report, we will use the term PGE reef to refer to the PGE-enriched mineralization, not the host rock layer. Within a layered igneous intrusion, reef-type mineralization is laterally persistent along strike, extending for the length of the intrusion, typically tens to hundreds of kilometers. However, the mineralized interval is thin, generally centimeters to meters thick, relative to the stratigraphic thickness of layers in an intrusion that vary from hundreds to thousands of meters. PGE-enriched sulfide mineralization is also found near the contacts or margins of layered mafic to ultramafic intrusions (Iljina and Lee, 2005). This contact-type mineralization consists of disseminated to massive concentrations of iron-copper-nickel-PGE-enriched sulfide mineral concentrations in zones that can be tens to hundreds

Network anomaly detection a machine learning perspective

CERN Document Server

Bhattacharyya, Dhruba Kumar

2013-01-01

With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents mach

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)

Intelligent Intrusion Detection of Grey Hole and Rushing Attacks in Self-Driving Vehicular Networks

Directory of Open Access Journals (Sweden)

Khattab M. Ali Alheeti

2016-07-01

Full Text Available Vehicular ad hoc networks (VANETs play a vital role in the success of self-driving and semi self-driving vehicles, where they improve safety and comfort. Such vehicles depend heavily on external communication with the surrounding environment via data control and Cooperative Awareness Messages (CAMs exchanges. VANETs are potentially exposed to a number of attacks, such as grey hole, black hole, wormhole and rushing attacks. This work presents an intelligent Intrusion Detection System (IDS that relies on anomaly detection to protect the external communication system from grey hole and rushing attacks. These attacks aim to disrupt the transmission between vehicles and roadside units. The IDS uses features obtained from a trace file generated in a network simulator and consists of a feed-forward neural network and a support vector machine. Additionally, the paper studies the use of a novel systematic response, employed to protect the vehicle when it encounters malicious behaviour. Our simulations of the proposed detection system show that the proposed schemes possess outstanding detection rates with a reduction in false alarms. This safe mode response system has been evaluated using four performance metrics, namely, received packets, packet delivery ratio, dropped packets and the average end to end delay, under both normal and abnormal conditions.

Detecting Malicious Nodes in Medical Smartphone Networks Through Euclidean Distance-Based Behavioral Profiling

DEFF Research Database (Denmark)

Meng, Weizhi; Li, Wenjuan; Wang, Yu

2017-01-01

and healthcare personnel. The underlying network architecture to support such devices is also referred to as medical smartphone networks (MSNs). Similar to other networks, MSNs also suffer from various attacks like insider attacks (e.g., leakage of sensitive patient information by a malicious insider......). In this work, we focus on MSNs and design a trust-based intrusion detection approach through Euclidean distance-based behavioral profiling to detect malicious devices (or called nodes). In the evaluation, we collaborate with healthcare organizations and implement our approach in a real simulated MSN...

Host based internet protocol (IP) packet analysis to enhance network security

International Nuclear Information System (INIS)

Ahmad, T.; Ahmad, S.Z.; Yasin, M.M.

2007-01-01

Data communication in a computer network environment is facing serious security threats from numerous sources such as viruses, worms, Zombies etc. These threats can be broadly characterized as internal or external security threats. Internal threats are mainly attributed to sneaker-nets, utility modems and unauthorized users, which can be minimized by skillful network administration, password management and optimum usage policy definition. The external threats need more serious attention as these attacks are mostly coming from public networks such as Internet. Frequency and complexity of such attacks is much higher as compared to internal attacks. This paper presents a host based network layer screening of external and internal IP packets for logging, analyzing and real-time detection of possible IP spoofing and Denial of Service attacks. This work can also be used in tuning security rules definition for gateway firewalls. Software has been developed which intercepts IP traffic and analyses it with respect to integrity and origin of I P packet. The received IP packets are parsed and analyzed for possible signs of intrusion. The results show that by watching and categorizing composition of various transport protocol such as TCP, UDP, ICMP and others along with verifying the origin of received IP packet can help in devising real-time firewall rule and blocking possible external attack. This is highly desirable for fighting against zero day attacks and can result in a better Mean Time between Failures (MTBF) to increase the survivability of computer network. Used in a right context, packet screening and filtering can be a useful tool for provision of reliable and stable network services. (author)

Is Host-Based Anomaly Detection + Temporal Correlation = Worm Causality

National Research Council Canada - National Science Library

Sekar, Vyas; Xie, Yinglian; Reiter, Michael K; Zhang, Hui

2007-01-01

Epidemic-spreading attacks (e.g., worm and botnet propagation) have a natural notion of attack causality - a single network flow causes a victim host to get infected and subsequently spread the attack...

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.

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.

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

Geological characters and petrological characters of metamorphosed medium-acidic intrusive complexes in Ludong Orogenic Belt,China

Institute of Scientific and Technical Information of China (English)

凌贤长; 胡庆立; 王丽霞

2002-01-01

Ludong orogenic belt in China is an importantal continent collision orogenic belt in eastern Asia, between Sino-Korean landmass and Yangtze landmass. The host rock of the orogenic belt is metamorphosed medium-acidic intrusive complexes, which can be divided into four types, that's, quartz dioritz, granite dioritz, monzonitic granite and undertint monzonitic granite, principal minerals are plagioclases, potassium feldspars and quartzs, minor minerals are hornblendes, biotites, clinopyxenes and garnets, accessory mineral types and assemblages are very similar, specially, various rocks are mainly fine-grained textures. They have the history of regional amphibolite facies metamorphism and deep-middle-shallow structural layer deformation, and are changed into various gneiss and tectonic system. There are many xenolithes of middle Proterozoic eclogite-host rock extrahigh-high pressure metamorphic complexes, a small xenolithes of early Proterozoic layered metamorphite system and granulites, and ultrabasic-basic rocks of various epoches in the metamorphosed medium-acidic intrusive complexes.

Host Event Based Network Monitoring

Energy Technology Data Exchange (ETDEWEB)

Jonathan Chugg

2013-01-01

The purpose of INL’s research on this project is to demonstrate the feasibility of a host event based network monitoring tool and the effects on host performance. Current host based network monitoring tools work on polling which can miss activity if it occurs between polls. Instead of polling, a tool could be developed that makes use of event APIs in the operating system to receive asynchronous notifications of network activity. Analysis and logging of these events will allow the tool to construct the complete real-time and historical network configuration of the host while the tool is running. This research focused on three major operating systems commonly used by SCADA systems: Linux, WindowsXP, and Windows7. Windows 7 offers two paths that have minimal impact on the system and should be seriously considered. First is the new Windows Event Logging API, and, second, Windows 7 offers the ALE API within WFP. Any future work should focus on these methods.

Is mindfulness-based therapy an effective intervention for obsessive-intrusive thoughts: a case series.

Science.gov (United States)

Wilkinson-Tough, Megan; Bocci, Laura; Thorne, Kirsty; Herlihy, Jane

2010-01-01

Despite the efficacy of cognitive-behavioural interventions in improving the experience of obsessions and compulsions, some people do not benefit from this approach. The present research uses a case series design to establish whether mindfulness-based therapy could benefit those experiencing obsessive-intrusive thoughts by targeting thought-action fusion and thought suppression. Three participants received a relaxation control intervention followed by a six-session mindfulness-based intervention which emphasized daily practice. Following therapy all participants demonstrated reductions in Yale-Brown Obsessive-Compulsive Scale scores to below clinical levels, with two participants maintaining this at follow-up. Qualitative analysis of post-therapy feedback suggested that mindfulness skills such as observation, awareness and acceptance were seen as helpful in managing thought-action fusion and suppression. Despite being limited by small participant numbers, these results suggest that mindfulness may be beneficial to some people experiencing intrusive unwanted thoughts and that further research could establish the possible efficacy of this approach in larger samples. Copyright (c) 2009 John Wiley & Sons, Ltd.

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

Science.gov (United States)

Hu, Haibin

2017-05-01

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

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.

Big Data Analytics for Flow-based Anomaly Detection in High-Speed Networks

OpenAIRE

Garofalo, Mauro

2017-01-01

The Cisco VNI Complete Forecast Highlights clearly states that the Internet traffic is growing in three different directions, Volume, Velocity, and Variety, bringing computer network into the big data era. At the same time, sophisticated network attacks are growing exponentially. Such growth making the existing signature-based security tools, like firewall and traditional intrusion detection systems, ineffective against new kind of attacks or variations of known attacks. In this dissertati...

A hierarchical detection method in external communication for self-driving vehicles based on TDMA

Science.gov (United States)

Al-ani, Muzhir Shaban; McDonald-Maier, Klaus

2018-01-01

Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms. PMID:29315302

A hierarchical detection method in external communication for self-driving vehicles based on TDMA.

Science.gov (United States)

Alheeti, Khattab M Ali; Al-Ani, Muzhir Shaban; McDonald-Maier, Klaus

2018-01-01

Security is considered a major challenge for self-driving and semi self-driving vehicles. These vehicles depend heavily on communications to predict and sense their external environment used in their motion. They use a type of ad hoc network termed Vehicular ad hoc networks (VANETs). Unfortunately, VANETs are potentially exposed to many attacks on network and application level. This paper, proposes a new intrusion detection system to protect the communication system of self-driving cars; utilising a combination of hierarchical models based on clusters and log parameters. This security system is designed to detect Sybil and Wormhole attacks in highway usage scenarios. It is based on clusters, utilising Time Division Multiple Access (TDMA) to overcome some of the obstacles of VANETs such as high density, high mobility and bandwidth limitations in exchanging messages. This makes the security system more efficient, accurate and capable of real time detection and quick in identification of malicious behaviour in VANETs. In this scheme, each vehicle log calculates and stores different parameter values after receiving the cooperative awareness messages from nearby vehicles. The vehicles exchange their log data and determine the difference between the parameters, which is utilised to detect Sybil attacks and Wormhole attacks. In order to realize efficient and effective intrusion detection system, we use the well-known network simulator (ns-2) to verify the performance of the security system. Simulation results indicate that the security system can achieve high detection rates and effectively detect anomalies with low rate of false alarms.

Growth of plutons by incremental emplacement of sheets in crystal-rich host: Evidence from Miocene intrusions of the Colorado River region, Nevada, USA

Science.gov (United States)

Miller, C.F.; Furbish, D.J.; Walker, B.A.; Claiborne, L.L.; Koteas, G.C.; Bleick, H.A.; Miller, J.S.

2011-01-01

Growing evidence supports the notion that plutons are constructed incrementally, commonly over long periods of time, yet field evidence for the multiple injections that seem to be required is commonly sparse or absent. Timescales of up to several million years, among other arguments, indicate that the dominant volume does not remain largely molten, yet if growing plutons are constructed from rapidly solidifying increments it is unlikely that intrusive contacts would escape notice. A model wherein magma increments are emplaced into melt-bearing but crystal-rich host, rather than either solid or crystal-poor material, provides a plausible explanation for this apparent conundrum. A partially solidified intrusion undoubtedly comprises zones with contrasting melt fraction and therefore strength. Depending on whether these zones behave elastically or ductilely in response to dike emplacement, intruding magma may spread to form sheets by either of two mechanisms. If the melt-bearing host is elastic on the relevant timescale, magma spreads rather than continuing to propagate upward, where it encounters a zone of higher rigidity (higher crystal fraction). Similarly, if the dike at first ascends through rigid, melt-poor material and then encounters a zone that is weak enough (poor enough in crystals) to respond ductilely, the ascending material will also spread because the dike tip ceases to propagate as in rigid material. We propose that ascending magma is thus in essence trapped, by either mechanism, within relatively crystal-poor zones. Contacts will commonly be obscure from the start because the contrast between intruding material (crystal-poorer magma) and host (crystal-richer material) is subtle, and they may be obscured even further by subsequent destabilization of the crystal-melt framework. Field evidence and zircon zoning stratigraphy in plutons of the Colorado River region of southern Nevada support the hypothesis that emplacement of magma replenishments into a

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

Semi-non-intrusive objective intelligibility measure using spatial filtering in hearing aids

DEFF Research Database (Denmark)

Sørensen, Charlotte; Boldt, Jesper Bünsow; Gran, Frederik

2016-01-01

-intrusive metrics have not been able to achieve acceptable intelligibility predictions. This paper presents a new semi-non-intrusive intelligibility measure based on an existing intrusive measure, STOI, where an estimate of the clean speech is extracted using spatial filtering in the hearing aid. The results......Reliable non-intrusive online assessment of speech intelligibility can play a key role for the functioning of hearing aids, e.g. as guidance for adjusting the hearing aid settings to the environment. While existing intrusive metrics can provide a precise and reliable measure, the current non...

Distributed Intrusion Sensor Using DFB Laser with Optical Feedback and Saturable Absorber

Directory of Open Access Journals (Sweden)

Kyoo Nam Choi

2018-01-01

Full Text Available Characteristics of a distributed intrusion sensor using a coherent DFB laser diode with an external optical feedback and saturable absorber were experimentally investigated. The stimulus at a location of 2 km using a PZT transducer placed the location of a simulated intruder in Φ-OTDR trace after averaging 32 times. Field trials demonstrated the detection of a vehicle and a pedestrian crossing above the sensing line and a loop in a burial depth of 50 cm. This distributed intrusion sensor using a coherent DFB laser diode as the light source had the advantages of a simple structure and intruder detection capability at the underground burial location.

A proposed HTTP service based IDS

Directory of Open Access Journals (Sweden)

Mohamed M. Abd-Eldayem

2014-03-01

Full Text Available The tremendous growth of the web-based applications has increased information security vulnerabilities over the Internet. Security administrators use Intrusion-Detection System (IDS to monitor network traffic and host activities to detect attacks against hosts and network resources. In this paper IDS based on Naïve Bayes classifier is analyzed. The main objective is to enhance IDS performance through preparing the training data set allowing to detect malicious connections that exploit the http service. Results of application are demonstrated and discussed. In the training phase of the proposed IDS, at first a feature selection technique based on Naïve Bayes classifier is used, this technique identifies the most important HTTP traffic features that can be used to detect HTTP attacks. In the testing and running phases proposed IDS classifies the network traffic based on the requested service, then based on the selected features Naïve Bayes classifier is used to analyze the HTTP service based traffic and identifies the HTTP normal connections and attacks. The performance of the IDS is measured through experiments using NSL-KDD data set. The results show that the detection rate of the IDS is about 99%, the false-positive rate is about 1%, and the false-negative rate is about 0.25%; therefore, proposed IDS holds the highest detection rate and the lowest false alarm compared with other leading IDS. In addition, the proposed IDS based on Naïve Bayes is used to classify network connections as a normal or attack. And it holds a high detection rate and a low false alarm.

Notes on saltwater intrusion and trace element distribution in Metro Manila groundwaters

International Nuclear Information System (INIS)

Santos, G. Jr.; Ramos, A.F.; Fernandez, L.G.; Almoneda, R.V.; Garcia, T.Y.; Cruz, C.C.; Petrache, C.A.; Andal, T.T.; Alcantara, E.

1989-01-01

Preliminary analyses of waters for uranium and other trace elements from deepwells operated by the Metropolitan Waterworks and Sewerage System (MWSS) in Metro Manila were performed. Uranium, which ranged from 0.2 ppb to 6 ppb, was correlated with saltwater intrusion. Values >=0.8 ppb for uranium were considered indicative of saline water intrusion in the aquifers. Saline water intrusions in Malabon, Navotas, Paranaque, Las Pinas, Bacoor, Imus, Kawit, Pasig, Antipolo, San Mateo, Taguig, Cainta, Taytay, Alabang and Muntinlupa were noted. Most of these areas were also identified by MWSS as being affected by saltwater intrusion. Tritium values ranged from 0 (below detection limits) to 44 tritium units. Except for one well in Muntinlupa, all the values obtained were below the lower limit of detection of 30.83 T.U. Mercury contents in six well locations had values above the maximum limit set by the National Standards for Drinking Water. Four wells exceeded the permissible level for manganese while two wells had iron concentrations greater than the National Standards. Other trace element concentrations such as Cr, Pb, Zn, Co and Ni either did not exceed their permissible levels or were not included in the National Standards. (Auth.). 6 refs.; 1 tab.; 3 figs

System for Malicious Node Detection in IPv6-Based Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Kresimir Grgic

2016-01-01

Full Text Available The trend of implementing the IPv6 into wireless sensor networks (WSNs has recently occurred as a consequence of a tendency of their integration with other types of IP-based networks. The paper deals with the security aspects of these IPv6-based WSNs. A brief analysis of security threats and attacks which are present in the IPv6-based WSN is given. The solution to an adaptive distributed system for malicious node detection in the IPv6-based WSN is proposed. The proposed intrusion detection system is based on distributed algorithms and a collective decision-making process. It introduces an innovative concept of probability estimation for malicious behaviour of sensor nodes. The proposed system is implemented and tested through several different scenarios in three different network topologies. Finally, the performed analysis showed that the proposed system is energy efficient and has a good capability to detect malicious nodes.

Flow-based intrusion detection

NARCIS (Netherlands)

Sperotto, Anna

2010-01-01

The spread of 1-10Gbps technology has in recent years paved the way to a flourishing landscape of new, high-bandwidth Internet services. As users, we depend on the Internet in our daily life for simple tasks such as checking e-mails, but also for managing private and financial information. However,

Flow-Based Intrusion Detection

NARCIS (Netherlands)

Sperotto, Anna; Pras, Aiko

The spread of 1-10 Gbps technology has in recent years paved the way to a flourishing landscape of new, high-bandwidth Internet services.At the same time, we have also observed increasingly frequent and widely diversified attacks. To this threat, the research community has answered with a growing

OPNET/Simulink Based Testbed for Disturbance Detection in the Smart Grid

Energy Technology Data Exchange (ETDEWEB)

Sadi, Mohammad A. H. [University of Memphis; Dasgupta, Dipankar [ORNL; Ali, Mohammad Hassan [University of Memphis; Abercrombie, Robert K [ORNL

2015-01-01

The important backbone of the smart grid is the cyber/information infrastructure, which is primarily used to communicate with different grid components. A smart grid is a complex cyber physical system containing a numerous and variety number of sources, devices, controllers and loads. Therefore, the smart grid is vulnerable to grid related disturbances. For such dynamic system, disturbance and intrusion detection is a paramount issue. This paper presents a Simulink and Opnet based co-simulated platform to carry out a cyber-intrusion in cyber network for modern power systems and the smart grid. The IEEE 30 bus power system model is used to demonstrate the effectiveness of the simulated testbed. The experiments were performed by disturbing the circuit breakers reclosing time through a cyber-attack. Different disturbance situations in the considered test system are considered and the results indicate the effectiveness of the proposed co-simulated scheme.

Approach for Assessing Human Intrusion into a Radwaste Repository

International Nuclear Information System (INIS)

Cho, Dong Keun; Kim, Jung Woo; Jeong, Jong Tae; Baik, Min Hoon

2016-01-01

An approach to assess human intrusion into radwaste repository resulting from future human actions was proposed based on the common principals, requirements, and recommendations from IAEA, ICRP, and OECD/NEA, with the assumption that the intrusion occurs after loss of knowledge of the hazardous nature of the disposal facility. At first, the essential boundary conditions were derived on the basis of international recommendations, followed by overall approach to deal with inadvertent human intrusion. The essential premises were derived on the basis of international recommendations, followed by overall approach to deal with inadvertent human intrusion. The procedure to derive protective measures was also explained with four steps regarding how to derive safety framework, general measures, potential measures, and eventual protective measures on the basis of stylized scenarios. It is expected that the approach proposed in this study will be effectively used to reduce the potential for and/or consequence of human intrusion during entire processes of realization of disposal facility.

Process Flow Features as a Host-Based Event Knowledge Representation

Science.gov (United States)

2012-06-14

sequences of packets. The time window concept of observing past packets was used to model history or mem- ory. Having memory of past packets can increase the...network statistics ( IPv4 statistics and IPv6 statistics), and IP routing table information. 3.3.2 Data Preparation. The following subsections outlines...vol. 7, no. 1, pp. 3–35, 1999. 13. R. Kemmerer and G. Vigna, “Intrusion detection: a brief history and overview,” Computer, vol. 35, no. 4, pp. 27–30

Hacking the Cell: Network Intrusion and Exploitation by Adenovirus E1A.

Science.gov (United States)

King, Cason R; Zhang, Ali; Tessier, Tanner M; Gameiro, Steven F; Mymryk, Joe S

2018-05-01

As obligate intracellular parasites, viruses are dependent on their infected hosts for survival. Consequently, viruses are under enormous selective pressure to utilize available cellular components and processes to their own advantage. As most, if not all, cellular activities are regulated at some level via protein interactions, host protein interaction networks are particularly vulnerable to viral exploitation. Indeed, viral proteins frequently target highly connected "hub" proteins to "hack" the cellular network, defining the molecular basis for viral control over the host. This widespread and successful strategy of network intrusion and exploitation has evolved convergently among numerous genetically distinct viruses as a result of the endless evolutionary arms race between pathogens and hosts. Here we examine the means by which a particularly well-connected viral hub protein, human adenovirus E1A, compromises and exploits the vulnerabilities of eukaryotic protein interaction networks. Importantly, these interactions identify critical regulatory hubs in the human proteome and help define the molecular basis of their function. Copyright © 2018 King et al.

INVESTIGATION OF NEURAL NETWORK ALGORITHM FOR DETECTION OF NETWORK HOST ANOMALIES IN THE AUTOMATED SEARCH FOR XSS VULNERABILITIES AND SQL INJECTIONS

Directory of Open Access Journals (Sweden)

Y. D. Shabalin

2016-03-01

Full Text Available A problem of aberrant behavior detection for network communicating computer is discussed. A novel approach based on dynamic response of computer is introduced. The computer is suggested as a multiple-input multiple-output (MIMO plant. To characterize dynamic response of the computer on incoming requests a correlation between input data rate and observed output response (outgoing data rate and performance metrics is used. To distinguish normal and aberrant behavior of the computer one-class neural network classifieris used. General idea of the algorithm is shortly described. Configuration of network testbed for experiments with real attacks and their detection is presented (the automated search for XSS and SQL injections. Real found-XSS and SQL injection attack software was used to model the intrusion scenario. It would be expectable that aberrant behavior of the server will reveal itself by some instantaneous correlation response which will be significantly different from any of normal ones. It is evident that correlation picture of attacks from different malware running, the site homepage overriding on the server (so called defacing, hardware and software failures will differ from correlation picture of normal functioning. Intrusion detection algorithm is investigated to estimate false positive and false negative rates in relation to algorithm parameters. The importance of correlation width value and threshold value selection was emphasized. False positive rate was estimated along the time series of experimental data. Some ideas about enhancement of the algorithm quality and robustness were mentioned.

Magmatic Diversity of the Wehrlitic Intrusions in the Oceanic Lower Crust of the Northern Oman Ophiolite

Science.gov (United States)

Kaneko, R.; Adachi, Y.; Miyashita, S.

2014-12-01

The Oman ophiolite extends along the east coast of Oman, and is the world's largest and best-preserved slice of obducted oceanic lithosphere. The magmatic history of this ophiolite is complex and is generally regarded as having occurred in three stages (MOR magmatism, subduction magmatism and intraplate magmatism). Wehrlitic intrusions constitute an important element of oceanic lower crust of the ophiolite, and numerous intrusions cut gabbro units in the northern Salahi block of this ophiolite. In this study area, we identified two different types of wehrlitic intrusions. One type of the intrusions mainly consists of dunite, plagioclase (Pl) wehrlite and mela-olivine (Ol) gabbro, in which the crystallization sequence is Ol followed by the contemporaneous crystallization of Pl and clinopyroxene (Cpx). This type is called "ordinary" wehrlitic intrusions and has similar mineral compositions to host gabbros (Adachi and Miyashita 2003; Kaneko et al. 2014). Another type of the intrusions is a single intrusion that crops out in an area 250 m × 150 m along Wadi Salahi. This intrusion consists of Pl-free "true" wehrlite, in which the crystallization sequence is Ol and then Cpx. The forsterite contents (Fo%) of Ol from the "ordinary" wehrlitic intrusions and "true" wehrlitic intrusions have ranges of 90.8-87.0 (NiO = 0.36-0.13 wt%) and 84.7 (NiO = 0.31 wt%), respectively. Cr numbers (Cr#) of Cr-spinel from the "true" wehrlitic intrusions show higher Cr# value of 0.85 than those of the "ordinary" wehrlitic intrusions (0.48-0.64). But the former is characterized by very high Fe3+ values (YFe3+ = 0.49-0.68). Kaneko et al. (2014) showed that the "ordinary" ubiquitous type has similar features to MOR magmatism and the depleted type in the Fizh block (Adachi and Miyashita 2003) links to subduction magmatism. These types are distinguished by their mineral chemistries (TiO2 and Na2O contents of Cpx). The TiO2 and Na2O contents of Cpx from the "true" wehrlitic intrusions have 0

Adaptive Intrusion Data System (AIDS)

International Nuclear Information System (INIS)

Corlis, N.E.

1980-05-01

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

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.

Multiple-Features-Based Semisupervised Clustering DDoS Detection Method

Directory of Open Access Journals (Sweden)

Yonghao Gu

2017-01-01

Full Text Available DDoS attack stream from different agent host converged at victim host will become very large, which will lead to system halt or network congestion. Therefore, it is necessary to propose an effective method to detect the DDoS attack behavior from the massive data stream. In order to solve the problem that large numbers of labeled data are not provided in supervised learning method, and the relatively low detection accuracy and convergence speed of unsupervised k-means algorithm, this paper presents a semisupervised clustering detection method using multiple features. In this detection method, we firstly select three features according to the characteristics of DDoS attacks to form detection feature vector. Then, Multiple-Features-Based Constrained-K-Means (MF-CKM algorithm is proposed based on semisupervised clustering. Finally, using MIT Laboratory Scenario (DDoS 1.0 data set, we verify that the proposed method can improve the convergence speed and accuracy of the algorithm under the condition of using a small amount of labeled data sets.

Non-intrusive optical study of gas and its exchange in human maxillary sinuses

Science.gov (United States)

Persson, L.; Andersson, M.; Svensson, T.; Cassel-Engquist, M.; Svanberg, K.; Svanberg, S.

2007-07-01

We demonstrate a novel non-intrusive technique based on tunable diode laser absorption spectroscopy to investigate human maxillary sinuses in vivo. The technique relies on the fact that free gases have much sharper absorption features (typical a few GHz) than the surrounding tissue. Molecular oxygen was detected at 760 nm. Volunteers have been investigated by injecting near-infrared light fibre-optically in contact with the palate inside the mouth. The multiply scattered light was detected externally by a handheld probe on and around the cheek bone. A significant signal difference in oxygen imprint was observed when comparing volunteers with widely different anamnesis regarding maxillary sinus status. Control measurements through the hand and through the cheek below the cheekbone were also performed to investigate any possible oxygen offset in the setup. These provided a consistently non-detectable signal level. The passages between the nasal cavity and the maxillary sinuses were also non-intrusively optically studied, to the best of our knowledge for the first time. These measurements provide information on the channel conductivity which may prove useful in facial sinus diagnostics. The results suggest that a clinical trial together with an ear-nose-throat (ENT) clinic should be carried out to investigate the clinical use of the new technique.

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

Use of Comparative Genomics-Based Markers for Discrimination of Host Specificity in Fusarium oxysporum.

Science.gov (United States)

van Dam, Peter; de Sain, Mara; Ter Horst, Anneliek; van der Gragt, Michelle; Rep, Martijn

2018-01-01

The polyphyletic nature of many formae speciales of Fusarium oxysporum prevents molecular identification of newly encountered strains based on conserved, vertically inherited genes. Alternative molecular detection methods that could replace labor- and time-intensive disease assays are therefore highly desired. Effectors are functional elements in the pathogen-host interaction and have been found to show very limited sequence diversity between strains of the same forma specialis , which makes them potential markers for host-specific pathogenicity. We therefore compared candidate effector genes extracted from 60 existing and 22 newly generated genome assemblies, specifically targeting strains affecting cucurbit plant species. Based on these candidate effector genes, a total of 18 PCR primer pairs were designed to discriminate between each of the seven Cucurbitaceae-affecting formae speciales When tested on a collection of strains encompassing different clonal lineages of these formae speciales , nonpathogenic strains, and strains of other formae speciales , they allowed clear recognition of the host range of each evaluated strain. Within Fusarium oxysporum f. sp. melonis more genetic variability exists than anticipated, resulting in three F. oxysporum f. sp. melonis marker patterns that partially overlapped with the cucurbit-infecting Fusarium oxysporum f. sp. cucumerinum , Fusarium oxysporum f. sp. niveum , Fusarium oxysporum f. sp. momordicae , and/or Fusarium oxysporum f. sp. lagenariae For F. oxysporum f. sp. niveum , a multiplex TaqMan assay was evaluated and was shown to allow quantitative and specific detection of template DNA quantities as low as 2.5 pg. These results provide ready-to-use marker sequences for the mentioned F. oxysporum pathogens. Additionally, the method can be applied to find markers distinguishing other host-specific forms of F. oxysporum IMPORTANCE Pathogenic strains of Fusarium oxysporum are differentiated into formae speciales based on

A 5-year follow-up case of multiple intrusive luxative injuries

Directory of Open Access Journals (Sweden)

Seema Thakur

2012-01-01

Full Text Available Introduction: Traumatic intrusive luxation is one of the most severe forms of dental injuries, usually affecting the maxillary incisors. The consequence of such an occurrence is a high risk of healing complications such as pulp necrosis, external inflammatory resorption, and external replacement resorption (ankylosis. Case Report: This report presents a case of severe intrusive luxation of multiple anterior teeth in an 11-year-old girl. The teeth were repositioned successfully by endodontic and orthodontic management. The case was monitored for 5 years. Discussion: Depending on the severity of the injury, different clinical approaches for treatment of intrusive luxation may be used. Despite the variety of treatment modalities, rehabilitation of intruded teeth is always a challenge and a multidisciplinary approach is important to achieve a successful result. In this case, intruded teeth were endodontically treated with multiple calcium hydroxide dressings and repositioned orthodontically. The follow-up of such cases is very important as the repair process after intrusion is complex. After 5 years, no clinical or radiographic pathology was detected.

Petrography and trace element signatures in silicates and Fe-Ti-oxides from the Lanjiahuoshan deposit, Panzhihua layered intrusion, Southwest China

Science.gov (United States)

Gao, Wenyuan; Ciobanu, Cristiana L.; Cook, Nigel J.; Huang, Fei; Meng, Lin; Gao, Shang

2017-12-01

Permian mafic-ultramafic layered intrusions in the central part of the Emeishan Large Igneous Province (ELIP), Southwestern China, host Fe-Ti-V-oxide ores that have features which distinguish them from other large layered intrusion-hosted deposits. The origin of these ores is highly debated. Careful petrographic examination, whole rock analysis, electron probe microanalysis, and measurement and mapping of trace element concentrations by laser ablation inductively coupled plasma mass spectrometry in all major and minor minerals (clinopyroxene, plagioclase, olivine, amphibole, titanomagnetite, ilmenite, pleonaste and pyrrhotite) has been undertaken on samples from the Lanjiahuoshan deposit, representing the Middle, Lower and Marginal Zone of the Panzhihua intrusion. Features are documented that impact on interpretation of intrusion petrology and with implications for genesis of the Fe-Ti-V-oxide ores. Firstly, there is evidence, as symplectites between clinopyroxene and plagioclase, for introduction of complex secondary melts. Secondly, reaction between a late hydrothermal fluid and clinopyroxene is recognized, which has led to formation of hydrated minerals (pargasite, phlogopite), as well as a potassium metasomatic event, postdating intrusion solidification, which led to formation of K-feldspar. Lastly, partitioning of trace elements between titanomagnetite and silicates needs to consider scavenging of metals by ilmenite (Mn, Sc, Zr, Nb, Sn, Hf and Ta) and sulfides, as well as the marked partitioning of Co, Ni, Zn, Ga, As and Sb into spinels exsolved from titanomagnetite. The role of these less abundant phases may have been understated in previous studies, highlighting the importance of petrographic examination of complex silicate-oxide-sulfide assemblages, as well as the need for a holistic approach to trace element analysis, acknowledging all minerals within the assemblage.

Modeling Thermal Pressurization Around Shallow Dikes Using Temperature-Dependent Hydraulic Properties: Implications for Deformation Around Intrusions

Science.gov (United States)

Townsend, Meredith R.

2018-01-01

Pressurization and flow of groundwater around igneous intrusions depend in part on the hydraulic diffusivity of the host rocks and processes that enhance diffusivity, such as fracturing, or decrease diffusivity, such as mineral precipitation during chemical alteration. Characterizing and quantifying the coupled effects of alteration, pore pressurization, and deformation have significant implications for deformation around intrusions, geothermal energy, contact metamorphism, and heat transfer at mid-ocean ridges. Fractures around dikes at Ship Rock, New Mexico, indicate that pore pressures in the host rocks exceeded hydrostatic conditions by at least 15 MPa following dike emplacement. Hydraulic measurements and petrographic analysis indicate that mineral precipitation clogged the pores of the host rock, reducing porosity from 0.25 to reducing permeability by 5 orders of magnitude. Field data from Ship Rock are used to motivate and constrain numerical models for thermal pore fluid pressurization adjacent to a meter-scale dike, using temperature-dependent hydraulic properties in the host rock as a proxy for porosity loss by mineral precipitation during chemical alteration. Reduction in permeability by chemical alteration has a negligible effect on pressurization. However, reduction in porosity by mineral precipitation increases fluid pressure by constricting pore volume and is identified as a potentially significant source of pressure. A scaling relationship is derived to determine when porosity loss becomes important; if permeability is low enough, pressurization by porosity loss outweighs pressurization by thermal expansion of fluids.

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....

Intrusion mechanics according to Burstone with the NiTi-SE-steel uprighting spring.

Science.gov (United States)

Sander, F G; Wichelhaus, A; Schiemann, C

1996-08-01

Intrusion mechanics according to Burstone can be regarded as a practicable method for the intrusion of incisors. 1. By applying the NiTi-SE-steel uprighting spring, relatively constant forces can be exerted over a large range of intrusion on both sides of the anterior tooth archwire. 2. By bending a 150 degrees tip-back bend or a curvature into the steel portion, the uprighting spring presented here is brought into the plastic range of the characteristic curve of force. 3. Application of sliding hooks on the intrusion spring permits readjustment for force transfer onto the anterior archwire. 4. Connecting the anterior archwire with the posterior elements by means of a steel ligature can be recommended only in some cases, because sagittally directed forces may be produced. 5. The adult patients presented showed an average intrusion of 0.6 mm/month, if a linear connection was presupposed. 6. An intrusive effect on the incisors could first be detected clinically after 6 to 8 weeks. 7. Application of a torque-key proves especially useful in controlling the incisor position during intrusion in order to avoid unnecessary radiography. 8. Actual prediction of the centre of resistance with the help of a cephalometric radiograph proved not to be feasible. 9. The calculated maximal intrusion of the mandibular incisors was 7 mm. 10. The torque-segmented archwire with crimped hooks and pseudoelastic springs between the molars and the crimped hooks proved very effective for retrusion and intrusion of maxillary incisors. The maxillary anterior teeth can be retruded by a total of 7 mm without readjustment. 11. Constant moments and forces could be transferred by applying preformed arch wires and segmented arch wires.

Enhanced Deployment Strategy for Role-based Hierarchical Application Agents in Wireless Sensor Networks with Established Clusterheads

Science.gov (United States)

Gendreau, Audrey

Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research, a model used to deploy intrusion detection capability on a Local Area Network (LAN), in the literature, was extended to develop a role-based hierarchical agent deployment algorithm for a WSN. The resulting model took into consideration the monitoring capability, risk, deployment distribution cost, and monitoring cost associated with each node. Changing the original LAN methodology approach to model a cluster-based sensor network depended on the ability to duplicate a specific parameter that represented the monitoring capability. Furthermore, other parameters derived from a LAN can elevate costs and risk of deployment, as well as jeopardize the success of an application on a WSN. A key component of the approach presented in this research was to reduce the costs when established clusterheads in the network were found to be capable of hosting additional detection agents. In addition, another cost savings component of the study addressed the reduction of vulnerabilities associated with deployment of agents to high volume nodes. The effectiveness of the presented method was validated by comparing it against a type of a power-based scheme that used each node's remaining energy as the deployment value. While available energy is directly related to the model used in the presented method, the study deliberately sought out nodes that were identified with having superior monitoring capability, cost less to create and sustain, and are at low-risk of an attack. This work investigated improving the efficiency of an intrusion detection system (IDS) by using the proposed model to deploy monitoring agents after a temperature sensing

Detection and response to unauthorized access to a communication device

Science.gov (United States)

Smith, Rhett; Gordon, Colin

2015-09-08

A communication gateway consistent with the present disclosure may detect unauthorized physical or electronic access and implement security actions in response thereto. A communication gateway may provide a communication path to an intelligent electronic device (IED) using an IED communications port configured to communicate with the IED. The communication gateway may include a physical intrusion detection port and a network port. The communication gateway may further include control logic configured to evaluate physical intrusion detection signal. The control logic may be configured to determine that the physical intrusion detection signal is indicative of an attempt to obtain unauthorized access to one of the communication gateway, the IED, and a device in communication with the gateway; and take a security action based upon the determination that the indication is indicative of the attempt to gain unauthorized access.

[The genetic diversity and homology of Anabaena azollae and its host plant (Azolla) based on rapd analysis].

Science.gov (United States)

Chen, Jian; Zheng, Wei-wen; Xu, Guo-zhong; Song, Tie-ying; Tang, Long-fei

2002-01-01

Symbiotic Anabeana azollae and its host plant Anabeana-free Azolla were isolated from 16 Azolla accessions representing different Azolla species or geographic origins.DNA polymorphic fragments were obtained by simultaneous RAPD amplification of both symbiont and host. The UPGMA clusters of Anabeana azollae and its host Azolla were established separately based on Dice coefficient caculation and a coordinated relationship was shown between Anabeana azollae and its Azolla host along both individual genetic divergence,but this genetic homology was reduced among different strains within Azolla species while the obvious mutants of Anabeana azollae were detected in some Azolla tested strains collected from different geographic area in the same host species.

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.

The Effects of Saltwater Intrusion to Flood Mitigation Project

Science.gov (United States)

Azida Abu Bakar, Azinoor; Khairudin Khalil, Muhammad

2018-03-01

The objective of this study is to determine the effects of saltwater intrusion to flood mitigation project located in the flood plains in the district of Muar, Johor. Based on the studies and designs carried out, one of the effective flood mitigation options identified is the Kampung Tanjung Olak bypass and Kampung Belemang bypass at the lower reaches of Sungai Muar. But, the construction of the Kampung Belemang and Tanjung Olak bypass, while speeding up flood discharges, may also increase saltwater intrusion during drought low flows. Establishing the dynamics of flooding, including replicating the existing situation and the performance with prospective flood mitigation interventions, is most effectively accomplished using computer-based modelling tools. The finding of this study shows that to overcome the problem, a barrage should be constructed at Sungai Muar to solve the saltwater intrusion and low yield problem of the river.

[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.

SQL injection detection system

OpenAIRE

Vargonas, Vytautas

2017-01-01

SQL injection detection system Programmers do not always ensure security of developed systems. That is why it is important to look for solutions outside being reliant on developers. In this work SQL injection detection system is proposed. The system analyzes HTTP request parameters and detects intrusions. It is based on unsupervised machine learning. Trained by regular request data system detects outlier user parameters. Since training is not reliant on previous knowledge of SQL injections, t...

A Non-Intrusive GMA Welding Process Quality Monitoring System Using Acoustic Sensing.

Science.gov (United States)

Cayo, Eber Huanca; Alfaro, Sadek Crisostomo Absi

2009-01-01

Most of the inspection methods used for detection and localization of welding disturbances are based on the evaluation of some direct measurements of welding parameters. This direct measurement requires an insertion of sensors during the welding process which could somehow alter the behavior of the metallic transference. An inspection method that evaluates the GMA welding process evolution using a non-intrusive process sensing would allow not only the identification of disturbances during welding runs and thus reduce inspection time, but would also reduce the interference on the process caused by the direct sensing. In this paper a nonintrusive method for weld disturbance detection and localization for weld quality evaluation is demonstrated. The system is based on the acoustic sensing of the welding electrical arc. During repetitive tests in welds without disturbances, the stability acoustic parameters were calculated and used as comparison references for the detection and location of disturbances during the weld runs.

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.

DNA-hosted copper nanoclusters/graphene oxide based fluorescent biosensor for protein kinase activity detection.

Science.gov (United States)

Wang, Mengke; Lin, Zihan; Liu, Qing; Jiang, Shan; Liu, Hua; Su, Xingguang

2018-07-05

A novel fluorescent biosensor for protein kinase activity (PKA) detection was designed by applying double-strands DNA-hosted copper nanoclusters (dsDNA-CuNCs) and graphene oxide (GO). One DNA strand of the dsDNA consisted of two domains, one domain can hybridize with another complementary DNA strand to stabilize the fluorescent CuNCs and another domain was adenosine 5'-triphosphate (ATP) aptamer. ATP aptamer of the dsDNA-CuNCs would be spontaneously absorbed onto the GO surface through π-π stacking interactions. Thus GO can efficiently quench the fluorescence (FL) of dsDNA-CuNCs through fluorescence resonance energy transfer (FRET). In the present of ATP, ATP specifically combined with ATP aptamer to form ATP-ATP aptamer binding complexes, which had much less affinity to GO, resulting in the fluorescence recovery of the system. Nevertheless, in the presence of PKA, ATP could be translated into ADP and ADP could not combine with ATP aptamer resulting in the fluorescence quenching of dsDNA-CuNCs again. According to the change of the fluorescence signal, PKA activity could be successfully monitored in the range of 0.1-5.0 U mL -1 with a detection limit (LOD) of 0.039 U mL -1 . Besides, the inhibitory effect of H-89 on PKA activity was studied. The sensor was performed for PKA activity detection in cell lysates with satisfactory results. Copyright © 2018 Elsevier B.V. All rights reserved.

A Proposal for Kelly CriterionBased Lossy Network Compression

Science.gov (United States)

2016-03-01

detection applications. Most of these applications only send alerts to the central analysis servers. These alerts do not provide the forensic capability...based intrusion detection systems. These systems tend to examine the indi- vidual system’s audit logs looking for intrusive activity. The notable

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.

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.

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.

Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

Science.gov (United States)

Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

2017-01-01

Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

[Simultaneous intrusion and retraction of the anterior teeth using a three-piece base arch].

Science.gov (United States)

Liu, D; Bai, D; Wang, C; Sun, W; Guo, J; Xi, R

2000-06-01

To evaluate the effects of the three-piece base arch on overbite correction of Class II malocclusion. 20 patients with high angle, flared incisors were treated using a three-piece base arch appliance. The intrusion force of four upper incisors was adjusted to approximately 50 g. The line of force action was 2 mm distally to the resistant center(RC) and the retraction force was 20 g, the right and left posterior segments were joined by a palatal bar. Cephalograms were taken before treatment (T1) and six months after treatment (T2). The upper molars moved mesially 0.60 +/- 0.35 mm and the distance of the vertical extrusion was 0.80 +/- 0.52 mm. The distances of the upper central incisor retraction and intrusion were -4.20 +/- 2.12 mm and 3.10 +/- 0.54 mm respectively. The RC of the central incisor retracted -4.12 +/- 1.96 mm and intruded 3.20 +/- 0.66 mm. The axial inclination of the upper incisor-palatal plane changed from 123.21 degrees +/- 4.26 degrees to 116.00 degrees +/- 3.96 degrees. The three-piece segmented approach can effectively intrude and retract the upper anterior teeth for flared incisors and deep overbite.

Fuzzy Kernel k-Medoids algorithm for anomaly detection problems

Science.gov (United States)

Rustam, Z.; Talita, A. S.

2017-07-01

Intrusion Detection System (IDS) is an essential part of security systems to strengthen the security of information systems. IDS can be used to detect the abuse by intruders who try to get into the network system in order to access and utilize the available data sources in the system. There are two approaches of IDS, Misuse Detection and Anomaly Detection (behavior-based intrusion detection). Fuzzy clustering-based methods have been widely used to solve Anomaly Detection problems. Other than using fuzzy membership concept to determine the object to a cluster, other approaches as in combining fuzzy and possibilistic membership or feature-weighted based methods are also used. We propose Fuzzy Kernel k-Medoids that combining fuzzy and possibilistic membership as a powerful method to solve anomaly detection problem since on numerical experiment it is able to classify IDS benchmark data into five different classes simultaneously. We classify IDS benchmark data KDDCup'99 data set into five different classes simultaneously with the best performance was achieved by using 30 % of training data with clustering accuracy reached 90.28 percent.

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

Zircon U-Pb dating of early Palaeozoic monzonitic intrusives from the Goonumbla area, New South Wales

International Nuclear Information System (INIS)

Butera, K.M.; Williams, I.S.; Blevin, P.L.; Simpson, C.J.

2001-01-01

Zircon U-Pb ages measured on four small intrusions into the succession of Ordovician volcanic rocks that hosts North Parkes Cu-Au mine northwest of Parkes. New South Wales. place limits on the age of the volcanic sequence. The basal Nelungaloo Volcanics are constrained by a cross-cutting monzodiorite to be ≥484.3 ± 2.9Ma (Early Ordovician). Similarly. the overlying basal Goonumbla Volcanics are constrained by another cross-cutting monzodiorite to be ≥450.8 ± 4.2Ma (Middle Ordovician). A later generation of monzonites intruded into the middle and upper Goonumbla Volcanics yield ages of 439.1 ± 4.5 and 438.9 ± 4.7 Ma (Siluro-Ordovician). These various ages are consistent with the ages of fossiliferous sediments within the volcanic sequence. and indicate that both the intrusive and volcanic rocks span an appreciable period of time-neither are the product of a single magmatic episode. Intrusion of the youngest monzonites and mineralisation was virtually contemporaneous. Copyright (2001) Geological Society of Australia

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

Intrusion detection method based on nonlinear correlation measure

NARCIS (Netherlands)

Ambusaidi, Mohammed A.; Tan, Zhiyuan; He, Xiangjian; Nanda, Priyadarsi; Lu, Liang Fu; Jamdagni, Aruna

2014-01-01

Cyber crimes and malicious network activities have posed serious threats to the entire internet and its users. This issue is becoming more critical, as network-based services, are more widespread and closely related to our daily life. Thus, it has raised a serious concern in individual internet

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...

VERSE: a novel approach to detect virus integration in host genomes through reference genome customization.

Science.gov (United States)

Wang, Qingguo; Jia, Peilin; Zhao, Zhongming

2015-01-01

Fueled by widespread applications of high-throughput next generation sequencing (NGS) technologies and urgent need to counter threats of pathogenic viruses, large-scale studies were conducted recently to investigate virus integration in host genomes (for example, human tumor genomes) that may cause carcinogenesis or other diseases. A limiting factor in these studies, however, is rapid virus evolution and resulting polymorphisms, which prevent reads from aligning readily to commonly used virus reference genomes, and, accordingly, make virus integration sites difficult to detect. Another confounding factor is host genomic instability as a result of virus insertions. To tackle these challenges and improve our capability to identify cryptic virus-host fusions, we present a new approach that detects Virus intEgration sites through iterative Reference SEquence customization (VERSE). To the best of our knowledge, VERSE is the first approach to improve detection through customizing reference genomes. Using 19 human tumors and cancer cell lines as test data, we demonstrated that VERSE substantially enhanced the sensitivity of virus integration site detection. VERSE is implemented in the open source package VirusFinder 2 that is available at http://bioinfo.mc.vanderbilt.edu/VirusFinder/.

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....

Management of multiple intrusive luxative injuries: A case report with 7-year follow-up

Directory of Open Access Journals (Sweden)

Seema Thakur

2014-01-01

Full Text Available This report presents a case of severe intrusive luxation of multiple anterior teeth in an 11-year-old girl. The teeth were repositioned successfully by endodontic and orthodontic management. The case was monitored for 7 years. Depending on the severity of the injury, different clinical approaches for treatment of intrusive luxation may be used. Despite the variety of treatment modalities, rehabilitation of intruded teeth is always a challenge and a multidisciplinary approach is important to achieve a successful result. In this case, intruded teeth were endodontically treated with multiple calcium hydroxide dressings and repositioned orthodontically. The follow-up of such cases is very important as the repair process after intrusion is complex. After 7 years, no clinical or radiographic pathology was detected.

A Novel Immune-Inspired Shellcode Detection Algorithm Based on Hyperellipsoid Detectors

Directory of Open Access Journals (Sweden)

Tianliang Lu

2018-01-01

Full Text Available Shellcodes are machine language codes injected into target programs in the form of network packets or malformed files. Shellcodes can trigger buffer overflow vulnerability and execute malicious instructions. Signature matching technology used by antivirus software or intrusion detection system has low detection rate for unknown or polymorphic shellcodes; to solve such problem, an immune-inspired shellcode detection algorithm was proposed, named ISDA. Static analysis and dynamic analysis were both applied. The shellcodes were disassembled to assembly instructions during static analysis and, for dynamic analysis, the API function sequences of shellcodes were obtained by simulation execution to get the behavioral features of polymorphic shellcodes. The extracted features of shellcodes were encoded to antigens based on n-gram model. Immature detectors become mature after immune tolerance based on negative selection algorithm. To improve nonself space coverage rate, the immune detectors were encoded to hyperellipsoids. To generate better antibody offspring, the detectors were optimized through clonal selection algorithm with genetic mutation. Finally, shellcode samples were collected and tested, and result shows that the proposed method has higher detection accuracy for both nonencoded and polymorphic shellcodes.

Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

Directory of Open Access Journals (Sweden)

Shameng Wen

Full Text Available Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

Microscopy-based Assays for High-throughput Screening of Host Factors Involved in Brucella Infection of Hela Cells.

Science.gov (United States)

Casanova, Alain; Low, Shyan H; Emmenlauer, Mario; Conde-Alvarez, Raquel; Salcedo, Suzana P; Gorvel, Jean-Pierre; Dehio, Christoph

2016-08-05

Brucella species are facultative intracellular pathogens that infect animals as their natural hosts. Transmission to humans is most commonly caused by direct contact with infected animals or by ingestion of contaminated food and can lead to severe chronic infections. Brucella can invade professional and non-professional phagocytic cells and replicates within endoplasmic reticulum (ER)-derived vacuoles. The host factors required for Brucella entry into host cells, avoidance of lysosomal degradation, and replication in the ER-like compartment remain largely unknown. Here we describe two assays to identify host factors involved in Brucella entry and replication in HeLa cells. The protocols describe the use of RNA interference, while alternative screening methods could be applied. The assays are based on the detection of fluorescently labeled bacteria in fluorescently labeled host cells using automated wide-field microscopy. The fluorescent images are analyzed using a standardized image analysis pipeline in CellProfiler which allows single cell-based infection scoring. In the endpoint assay, intracellular replication is measured two days after infection. This allows bacteria to traffic to their replicative niche where proliferation is initiated around 12 hr after bacterial entry. Brucella which have successfully established an intracellular niche will thus have strongly proliferated inside host cells. Since intracellular bacteria will greatly outnumber individual extracellular or intracellular non-replicative bacteria, a strain constitutively expressing GFP can be used. The strong GFP signal is then used to identify infected cells. In contrast, for the entry assay it is essential to differentiate between intracellular and extracellular bacteria. Here, a strain encoding for a tetracycline-inducible GFP is used. Induction of GFP with simultaneous inactivation of extracellular bacteria by gentamicin enables the differentiation between intracellular and extracellular

Integrated Detection of Pathogens and Host Biomarkers for Wounds

Energy Technology Data Exchange (ETDEWEB)

Jaing, C

2012-03-19

The increasing incidence and complications arising from combat wounds has necessitated a reassessment of methods for effective treatment. Infection, excessive inflammation, and incidence of drug-resistant organisms all contribute toward negative outcomes for afflicted individuals. The organisms and host processes involved in wound progression, however, are incompletely understood. We therefore set out, using our unique technical resources, to construct a profile of combat wounds which did or did not successfully resolve. We employed the Lawrence Livermore Microbial Detection Array and identified a number of nosocomial pathogens present in wound samples. Some of these identities corresponded with bacterial isolates previously cultured, while others were not obtained via standard microbiology. Further, we optimized proteomics protocols for the identification of host biomarkers indicative of various stages in wound progression. In combination with our pathogen data, our biomarker discovery efforts will provide a profile corresponding to wound complications, and will assist significantly in treatment of these complex cases.

Review of the geochemistry and metallogeny of approximately 1.4 Ga granitoid intrusions of the conterminous United States

Science.gov (United States)

du Bray, Edward A.; Holm-Denoma, Christopher S.; Lund, Karen; Premo, Wayne R.

2018-03-27

The conterminous United States hosts numerous volumetrically significant and geographically dispersed granitoid intrusions that range in age from 1.50 to 1.32 billion years before present (Ga). Although previously referred to as A-type granites, most are better described as ferroan granites. These granitoid intrusions are distributed in the northern and central Rocky Mountains, the Southwest, the northern midcontinent, and a swath largely buried beneath Phanerozoic cover across the Great Plains and into the southern midcontinent. These intrusions, with ages that are bimodally distributed between about 1.455–1.405 Ga and 1.405–1.320 Ga, are dispersed nonsystematically with respect to age across their spatial extents. Globally, although A-type or ferroan granites are genetically associated with rare-metal deposits, most U.S. 1.4 Ga granitoid intrusions do not contain significant deposits. Exceptions are the light rare-earth element deposit at Mountain Pass, California, and the iron oxide-apatite and iron oxide-copper-gold deposits in southeast Missouri.Most of the U.S. 1.4 Ga granitoid intrusions are composed of hornblende ± biotite or biotite ± muscovite monzogranite, commonly with prominent alkali feldspar megacrysts; however, modal compositions vary widely. These intrusions include six of the eight commonly identified subtypes of ferroan granite: alkali-calcic and calc-alkalic peraluminous subtypes; alkalic, alkali-calcic, and calc-alkalic metaluminous subtypes; and the alkalic peralkaline subtype. The U.S. 1.4 Ga granitoid intrusions also include variants of these subtypes that have weakly magnesian compositions. Extreme large-ion lithophile element enrichments typical of ferroan granites elsewhere are absent among these intrusions. Chondrite-normalized rare-earth element patterns for these intrusions have modest negative slopes and moderately developed negative europium anomalies. Their radiogenic isotopic compositions are consistent with mixing involving

Relationship between vapor intrusion and human exposure to trichloroethylene.

Science.gov (United States)

Archer, Natalie P; Bradford, Carrie M; Villanacci, John F; Crain, Neil E; Corsi, Richard L; Chambers, David M; Burk, Tonia; Blount, Benjamin C

2015-01-01

Trichloroethylene (TCE) in groundwater has the potential to volatilize through soil into indoor air where it can be inhaled. The purpose of this study was to determine whether individuals living above TCE-contaminated groundwater are exposed to TCE through vapor intrusion. We examined associations between TCE concentrations in various environmental media and TCE concentrations in residents. For this assessment, indoor air, outdoor air, soil gas, and tap water samples were collected in and around 36 randomly selected homes; blood samples were collected from 63 residents of these homes. Additionally, a completed exposure survey was collected from each participant. Environmental and blood samples were analyzed for TCE. Mixed model multiple linear regression analyses were performed to determine associations between TCE in residents' blood and TCE in indoor air, outdoor air, and soil gas. Blood TCE concentrations were above the limit of quantitation (LOQ; ≥ 0.012 µg L(-1)) in 17.5% of the blood samples. Of the 36 homes, 54.3%, 47.2%, and >84% had detectable concentrations of TCE in indoor air, outdoor air, and soil gas, respectively. Both indoor air and soil gas concentrations were statistically significantly positively associated with participants' blood concentrations (P = 0.0002 and P = 0.04, respectively). Geometric mean blood concentrations of residents from homes with indoor air concentrations of >1.6 µg m(-3) were approximately 50 times higher than geometric mean blood TCE concentrations in participants from homes with no detectable TCE in indoor air (P < .0001; 95% CI 10.4-236.4). This study confirms the occurrence of vapor intrusion and demonstrates the magnitude of exposure from vapor intrusion of TCE in a residential setting.

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.

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.

Note on Studying Change Point of LRD Traffic Based on Li's Detection of DDoS Flood Attacking

Directory of Open Access Journals (Sweden)

Zhengmin Xia

2010-01-01

Full Text Available Distributed denial-of-service (DDoS flood attacks remain great threats to the Internet. To ensure network usability and reliability, accurate detection of these attacks is critical. Based on Li's work on DDoS flood attack detection, we propose a DDoS detection method by monitoring the Hurst variation of long-range dependant traffic. Specifically, we use an autoregressive system to estimate the Hurst parameter of normal traffic. If the actual Hurst parameter varies significantly from the estimation, we assume that DDoS attack happens. Meanwhile, we propose two methods to determine the change point of Hurst parameter that indicates the occurrence of DDoS attacks. The detection rate associated with one method and false alarm rate for the other method are also derived. The test results on DARPA intrusion detection evaluation data show that the proposed approaches can achieve better detection performance than some well-known self-similarity-based detection methods.

An Excel®-based visualization tool of 2-D soil gas concentration profiles in petroleum vapor intrusion.

Science.gov (United States)

Verginelli, Iason; Yao, Yijun; Suuberg, Eric M

2016-01-01

In this study we present a petroleum vapor intrusion tool implemented in Microsoft ® Excel ® using Visual Basic for Applications (VBA) and integrated within a graphical interface. The latter helps users easily visualize two-dimensional soil gas concentration profiles and indoor concentrations as a function of site-specific conditions such as source strength and depth, biodegradation reaction rate constant, soil characteristics and building features. This tool is based on a two-dimensional explicit analytical model that combines steady-state diffusion-dominated vapor transport in a homogeneous soil with a piecewise first-order aerobic biodegradation model, in which rate is limited by oxygen availability. As recommended in the recently released United States Environmental Protection Agency's final Petroleum Vapor Intrusion guidance, a sensitivity analysis and a simplified Monte Carlo uncertainty analysis are also included in the spreadsheet.

Respon Konsumen pada Mobile Advergames: Intrusiveness dan Irritation

Directory of Open Access Journals (Sweden)

Sony Kusumasondjaja

2016-12-01

Full Text Available Abstract. Increasing adoption of mobile advergames to deliver marketing messages has not been followed by empirical findings to support its effectiveness. This research attempts to examine the effect of mobile advergames intrusiveness on consumer irritation, attitudes, and purchase intention. This investigation on mobile advergame effectiveness was based on the increasing use of mobile media to deliver marketing messages to consumers from different demographic background. Conceptual framework was developed based on Advertising Avoidance Theory. For data collection, self-administered survey was conducted by adopting purposive sampling involving 213 respondents residing in Surabaya who have had experience in playing mobile game as respondents. Results indicate that intrusiveness positively affects consumer irritation. Consumer irritation negatively affects attitude towards the mobile advergames and attitude towards the advertised product. The better the consumer attitude towards the mobile advergames, the more positive the attitude towards the advertised product. Moreover, the more positive the attitude towards the advertised product, the greater the consumer intention to purchase. Interestingly, consumer attitude toward the mobile advergames has insignificant influence on purchase intention. Findings of the study offer significant contribution to marketing practices using mobile advergames as media placement in their advertising strategy. Keywords: intrusiveness, irritation, mobile advergames, attitude, advertising

Simulation of sea water intrusion in coastal aquifers

Indian Academy of Sciences (India)

dependent miscible flow and transport modelling approach for simulation of seawater intrusion in coastal aquifers. A nonlinear optimization-based simulation methodology was used in this study. Various steady state simulations are performed for a ...

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

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

A Cyber-Attack Detection Model Based on Multivariate Analyses

Science.gov (United States)

Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

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.

A 10-year Ground-Based Radar Climatology of Convective Penetration of Stratospheric Intrusions and Associated Large-Scale Transport over the CONUS

Science.gov (United States)

Homeyer, C. R.

2017-12-01

Deep convection reaching the upper troposphere and lower stratosphere (UTLS) and its impact on atmospheric composition through rapid vertical transport of lower troposphere air and stratosphere-troposphere exchange has received increasing attention in the past 5-10 years. Most efforts focused on convection have been directed toward storms that reach and/or penetrate the coincident environmental lapse-rate tropopause. However, convection has also been shown to reach into large-scale stratospheric intrusions (depressions of stratospheric air lying well below the lapse-rate tropopause on the cyclonic side of upper troposphere jet streams). Such convective penetration of stratospheric intrusions is not captured by studies of lapse-rate tropopause-penetrating convection. In this presentation, it will be shown using hourly, high-quality mergers of ground-based radar observations from 2004 to 2013 in the contiguous United States (CONUS) and forward large-scale trajectory analysis that convective penetration of stratospheric intrusions: 1) is more frequent than lapse-rate tropopause-penetrating convection, 2) occurs over a broader area of the CONUS than lapse-rate tropopause-penetrating convection, and 3) can influence the composition of the lower stratosphere through large-scale advection of convectively influenced air to altitudes above the lapse-rate tropopause, which we find to occur for about 8.5% of the intrusion volumes reached by convection.

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

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.

Treatment of Intrusive Suicidal Imagery Using Eye Movements

Directory of Open Access Journals (Sweden)

Jaël S. van Bentum

2017-06-01

Full Text Available Suicide and suicidal behavior are major public health concerns, and affect 3–9% of the population worldwide. Despite increased efforts for national suicide prevention strategies, there are still few effective interventions available for reducing suicide risk. In this article, we describe various theoretical approaches for suicide ideation and behavior, and propose to examine the possible effectiveness of a new and innovative preventive strategy. A model of suicidal intrusion (mental imagery related to suicide, also referred to as suicidal flash-forwards is presented describing one of the assumed mechanisms in the etiology of suicide and the mechanism of therapeutic change. We provide a brief rationale for an Eye Movement Dual Task (EMDT treatment for suicidal intrusions, describing techniques that can be used to target these suicidal mental images and thoughts to reduce overall behavior. Based on the available empirical evidence for the mechanisms of suicidal intrusions, this approach appears to be a promising new treatment to prevent suicidal behavior as it potentially targets one of the linking pins between suicidal ideation and suicidal actions.

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.

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.

Description of a nanobody-based competitive immunoassay to detect tsetse fly exposure.

Directory of Open Access Journals (Sweden)

Guy Caljon

2015-02-01

Full Text Available Tsetse flies are the main vectors of human and animal African trypanosomes. The Tsal proteins in tsetse fly saliva were previously identified as suitable biomarkers of bite exposure. A new competitive assay was conceived based on nanobody (Nb technology to ameliorate the detection of anti-Tsal antibodies in mammalian hosts.A camelid-derived Nb library was generated against the Glossina morsitans morsitans sialome and exploited to select Tsal specific Nbs. One of the three identified Nb families (family III, TsalNb-05 and TsalNb-11 was found suitable for anti-Tsal antibody detection in a competitive ELISA format. The competitive ELISA was able to detect exposure to a broad range of tsetse species (G. morsitans morsitans, G. pallidipes, G. palpalis gambiensis and G. fuscipes and did not cross-react with the other hematophagous insects (Stomoxys calcitrans and Tabanus yao. Using a collection of plasmas from tsetse-exposed pigs, the new test characteristics were compared with those of the previously described G. m. moristans and rTsal1 indirect ELISAs, revealing equally good specificities (> 95% and positive predictive values (> 98% but higher negative predictive values and hence increased sensitivity (> 95% and accuracy (> 95%.We have developed a highly accurate Nb-based competitive immunoassay to detect specific anti-Tsal antibodies induced by various tsetse fly species in a range of hosts. We propose that this competitive assay provides a simple serological indicator of tsetse fly presence without the requirement of test adaptation to the vertebrate host species. In addition, the use of monoclonal Nbs for antibody detection is innovative and could be applied to other tsetse fly salivary biomarkers in order to achieve a multi-target immunoprofiling of hosts. In addition, this approach could be broadened to other pathogenic organisms for which accurate serological diagnosis remains a bottleneck.

Non-intrusive long-term monitoring approaches

International Nuclear Information System (INIS)

Smathers, D.; Mangan, D.

1998-01-01

In order to promote internatinal confidence that the US and Russia are disarming per their commitments under Article 6 of the Non-Proliferation Treaty, an international verification regime may be applied to US and Russian excess fissile materials. Initially, it is envisioned that this verification regime would be applied at storage facilities; however, it should be anticipated that the verification regime would continue throughout any material disposition activities, should such activities be pursued. once the materials are accepted into the verification regime, it is assumed that long term monitoring will be used to maintain continuity of knowledge. The requirements for long term storage monitoring include unattended operation for extended periods of time, minimal intrusiveness on the host nation's safety and security activities, data collection incorporating data authentication, and monitoring redundancy to allow resolution of anomalies and to continue coverage in the event of equipment failures. Additional requirements include effective data review and analysis processes, operation during storage facility loading, procedure for removal of inventory items for safety-related surveillance, and low cost, reliable equipment. A monitoring system might include both continuous monitoring of storagecontainers and continuous area monitoring. These would be complemented with periodic on-site inspections. A fissile material storage facility is not a static operation. The initial studies have shown there are a number of valid reasons why a host nation may need them to remove material from the storage facility. A practical monitoring system must be able to accommodate necessary material movements

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.

Saline water intrusion toward groundwater: Issues and its control

Directory of Open Access Journals (Sweden)

Purnama S

2012-10-01

Full Text Available Nowadays, saline water pollution has been gaining its importance as the major issue around the world, especially in the urban coastal area. Saline water pollution has major impact on human life and livelihood. It ́s mainly a result from static fossil water and the dynamics of sea water intrusion. The problem of saline water pollution caused by seawater intrusion has been increasing since the beginning of urban population. The problem of sea water intrusion in the urban coastal area must be anticipated as soon as possible especially in the urban areas developed in coastal zones,. This review article aims to; (i analyze the distribution of saline water pollution on urban coastal area in Indonesia and (ii analyze some methods in controlling saline water pollution, especially due to seawater intrusion in urban coastal area. The strength and weakness of each method have been compared, including (a applying different pumping patterns, (b artificial recharge, (c extraction barrier, (d injection barrier and (e subsurface barrier. The best method has been selected considering its possible development in coastal areas of developing countries. The review is based considering the location of Semarang coastal area, Indonesia. The results have shown that artificial recharge and extraction barrier are the most suitable methods to be applied in the area.

Lunar floor-fractured craters: Modes of dike and sill emplacement and implications of gas production and intrusion cooling on surface morphology and structure

Science.gov (United States)

Wilson, Lionel; Head, James W.

2018-05-01

Lunar floor-fractured craters (FFCs) represent the surface manifestation of a class of shallow crustal intrusions in which magma-filled cracks (dikes) rising to the surface from great depth encounter contrasts in host rock lithology (breccia lens, rigid solidified melt sheet) and intrude laterally to form a sill, laccolith or bysmalith, thereby uplifting and deforming the crater floor. Recent developments in the knowledge of lunar crustal thickness and density structure have enabled important revisions to models of the generation, ascent and eruption of magma, and new knowledge about the presence and behavior of magmatic volatiles has provided additional perspectives on shallow intrusion processes in FFCs. We use these new data to assess the processes that occur during dike and sill emplacement with particular emphasis on tracking the fate and migration of volatiles and their relation to candidate venting processes. FFCs result when dikes are capable of intruding close to the surface, but fail to erupt because of the substructure of their host impact craters, and instead intrude laterally after encountering a boundary where an increase in ductility (base of breccia lens) or rigidity (base of solidified melt sheet) occurs. Magma in dikes approaching the lunar surface experiences increasingly lower overburden pressures: this enhances CO gas formation and brings the magma into the realm of the low pressure release of H2O and sulfur compounds, both factors adding volatiles to those already collected in the rising low-pressure part of the dike tip. High magma rise velocity is driven by the positive buoyancy of the magma in the part of the dike remaining in the mantle. The dike tip overshoots the interface and the consequent excess pressure at the interface drives the horizontal flow of magma to form the intrusion and raise the crater floor. If sill intrusion were controlled by the physical properties at the base of the melt sheet, dikes would be required to approach to

Evaluation by latent class analysis of a magnetic capture based DNA extraction followed by real-time qPCR as a new diagnostic method for detection of Echinococcus multilocularis in definitive hosts.

Science.gov (United States)

Maas, Miriam; van Roon, Annika; Dam-Deisz, Cecile; Opsteegh, Marieke; Massolo, Alessandro; Deksne, Gunita; Teunis, Peter; van der Giessen, Joke

2016-10-30

A new method, based on a magnetic capture based DNA extraction followed by qPCR, was developed for the detection of the zoonotic parasite Echinococcus multilocularis in definitive hosts. Latent class analysis was used to compare this new method with the currently used phenol-chloroform DNA extraction followed by single tube nested PCR. In total, 60 red foxes and coyotes from three different locations were tested with both molecular methods and the sedimentation and counting technique (SCT) or intestinal scraping technique (IST). Though based on a limited number of samples, it could be established that the magnetic capture based DNA extraction followed by qPCR showed similar sensitivity and specificity as the currently used phenol-chloroform DNA extraction followed by single tube nested PCR. All methods have a high specificity as shown by Bayesian latent class analysis. Both molecular assays have higher sensitivities than the combined SCT and IST, though the uncertainties in sensitivity estimates were wide for all assays tested. The magnetic capture based DNA extraction followed by qPCR has the advantage of not requiring hazardous chemicals like the phenol-chloroform DNA extraction followed by single tube nested PCR. This supports the replacement of the phenol-chloroform DNA extraction followed by single tube nested PCR by the magnetic capture based DNA extraction followed by qPCR for molecular detection of E. multilocularis in definitive hosts. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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.

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

Cultural syndromes and age moderate the emotional impact of illness intrusiveness in rheumatoid arthritis.

Science.gov (United States)

Devins, Gerald M; Gupta, Anita; Cameron, Jill; Woodend, Kirsten; Mah, Kenneth; Gladman, Dafna

2009-02-01

The authors investigated cultural syndromes (multidimensional vectors comprising culturally based attitudes, values, and beliefs) and age as moderators of the emotional impact of illness intrusiveness--illness-induced lifestyle disruptions--in rheumatoid arthritis (RA) and examined illness intrusiveness effects in total and separately for three life domains (relationships and personal development, intimacy, and instrumental). People with RA (n = 105) completed the Illness Intrusiveness Ratings, Individualism-Collectivism, and Center for Epidemiologic Studies--Depression scales in a one-on-one interview. Controlling for disease and background characteristics, the association between illness intrusiveness (total score and the Relationships and Personal Development subscale) and distress was inverse when young adults with RA endorsed high horizontal individualism. Illness intrusiveness into intimacy was associated with increased distress, and this intensified when respondents endorsed high vertical individualism, horizontal collectivism, vertical collectivism, or low horizontal individualism. The negative emotional impact of illness intrusiveness into intimacy diminished with increasing age. Given an aging and increasingly pluralistic society, diversity can no longer be ignored in addressing the psychosocial impact of chronic, disabling disease.

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)

Entropy-Based Application Layer DDoS Attack Detection Using Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Khundrakpam Johnson Singh

2016-10-01

Full Text Available Distributed denial-of-service (DDoS attack is one of the major threats to the web server. The rapid increase of DDoS attacks on the Internet has clearly pointed out the limitations in current intrusion detection systems or intrusion prevention systems (IDS/IPS, mostly caused by application-layer DDoS attacks. Within this context, the objective of the paper is to detect a DDoS attack using a multilayer perceptron (MLP classification algorithm with genetic algorithm (GA as learning algorithm. In this work, we analyzed the standard EPA-HTTP (environmental protection agency-hypertext transfer protocol dataset and selected the parameters that will be used as input to the classifier model for differentiating the attack from normal profile. The parameters selected are the HTTP GET request count, entropy, and variance for every connection. The proposed model can provide a better accuracy of 98.31%, sensitivity of 0.9962, and specificity of 0.0561 when compared to other traditional classification models.

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

Assessment of groundwater vulnerability to anthropogenic pollution and seawater intrusion in a small tropical island using index-based methods.

Science.gov (United States)

Kura, Nura Umar; Ramli, Mohammad Firuz; Ibrahim, Shaharin; Sulaiman, Wan Nor Azmin; Aris, Ahmad Zaharin; Tanko, Adamu Idris; Zaudi, Muhammad Amar

2015-01-01

In this work, the DRASTIC and GALDIT models were employed to determine the groundwater vulnerability to contamination from anthropogenic activities and seawater intrusion in Kapas Island. In addition, the work also utilized sensitivity analysis to evaluate the influence of each individual parameter used in developing the final models. Based on these effects and variation indices of the said parameters, new effective weights were determined and were used to create modified DRASTIC and GALDIT models. The final DRASTIC model classified the island into five vulnerability classes: no risk (110-140), low (140-160), moderate (160-180), high (180-200), and very high (>200), covering 4, 26, 59, 4, and 7 % of the island, respectively. Likewise, for seawater intrusion, the modified GALDIT model delineates the island into four vulnerability classes: very low (130) covering 39, 33, 18, and 9 % of the island, respectively. Both models show that the areas that are likely to be affected by anthropogenic pollution and seawater intrusion are within the alluvial deposit at the western part of the island. Pearson correlation was used to verify the reliability of the two models in predicting their respective contaminants. The correlation matrix showed a good relationship between DRASTIC model and nitrate (r = 0.58). In a similar development, the correlation also reveals a very strong negative relationship between GALDIT model and seawater contaminant indicator (resistivity Ωm) values (r = -0.86) suggesting that the model predicts more than 86 % of seawater intrusion. In order to facilitate management strategy, suitable areas for artificial recharge were identified through modeling. The result suggested some areas within the alluvial deposit at the western part of the island as suitable for artificial recharge. This work can serve as a guide for a full vulnerability assessment to anthropogenic pollution and seawater intrusion in small islands and will help policy maker and

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.

LAN attack detection using Discrete Event Systems.

Science.gov (United States)

Hubballi, Neminath; Biswas, Santosh; Roopa, S; Ratti, Ritesh; Nandi, Sukumar

2011-01-01

Address Resolution Protocol (ARP) is used for determining the link layer or Medium Access Control (MAC) address of a network host, given its Internet Layer (IP) or Network Layer address. ARP is a stateless protocol and any IP-MAC pairing sent by a host is accepted without verification. This weakness in the ARP may be exploited by malicious hosts in a Local Area Network (LAN) by spoofing IP-MAC pairs. Several schemes have been proposed in the literature to circumvent these attacks; however, these techniques either make IP-MAC pairing static, modify the existing ARP, patch operating systems of all the hosts etc. In this paper we propose a Discrete Event System (DES) approach for Intrusion Detection System (IDS) for LAN specific attacks which do not require any extra constraint like static IP-MAC, changing the ARP etc. A DES model is built for the LAN under both a normal and compromised (i.e., spoofed request/response) situation based on the sequences of ARP related packets. Sequences of ARP events in normal and spoofed scenarios are similar thereby rendering the same DES models for both the cases. To create different ARP events under normal and spoofed conditions the proposed technique uses active ARP probing. However, this probing adds extra ARP traffic in the LAN. Following that a DES detector is built to determine from observed ARP related events, whether the LAN is operating under a normal or compromised situation. The scheme also minimizes extra ARP traffic by probing the source IP-MAC pair of only those ARP packets which are yet to be determined as genuine/spoofed by the detector. Also, spoofed IP-MAC pairs determined by the detector are stored in tables to detect other LAN attacks triggered by spoofing namely, man-in-the-middle (MiTM), denial of service etc. The scheme is successfully validated in a test bed. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Supramolecular Host-Guest System as Ratiometric Fe3+ Ion Sensor Based on Water-Soluble Pillar[5]arene.

Science.gov (United States)

Yao, Qianfang; Lü, Baozhong; Ji, Chendong; Cai, Yang; Yin, Meizhen

2017-10-18

Developing a specific, ratiometric, and reversible detection method for metal ions is significant to guard against the threat of metal-caused environmental pollution and organisms poisoning. Here a supramolecular host-guest system (WP5⊃G) based on water-soluble pillar[5]arene (WP5) and water-soluble quaternized perylene diimide derivative (G) was constructed. Morphological transformation was achieved during the process of adding WP5 into G aqueous solution, and a fluorescence "turn-off" phenomenon was observed which was caused by supramolecular photoinduced electron transfer (PET). Meanwhile, hydrophobic effect and electrostatic interaction played important roles in this supramolecular process, which was confirmed by isothermal titration calorimeter (ITC) and ζ potential experiments. Furthermore, the supramolecular host-guest system could be a "turn-on" fluorescent probe for Fe 3+ ion detection through the process of interdicting supramolecular PET. Moreover, the Fe 3+ ion detection showed specific, ratiometric, and reversible performances with a detection limit of 2.13 × 10 -7 M, which might have great potentials in biological and environmental monitoring.

Late Neoproterozoic layered mafic intrusion of arc-affinity in the Arabian-Nubian Shield: A case study from the Shahira layered mafic intrusion, southern Sinai, Egypt

Energy Technology Data Exchange (ETDEWEB)

Azer, M.K.; Obeid, M.A.; Gahalan, H.A.

2016-07-01

The Shahira Layered Mafic Intrusion (SLMI), which belongs to the late Neoproterozoic plutonic rocks of the Arabian-Nubian Shield, is the largest layered mafic intrusion in southern Sinai. Field relations indicate that it is younger than the surrounding metamorphic rocks and older than the post-orogenic granites. Based on variation in mineral paragenesis and chemical composition, the SLMI is distinguished into pyroxene-hornblende gabbro, hornblende gabbro and diorite lithologies. The outer zone of the mafic intrusion is characterized by fine-grained rocks (chilled margin gabbroic facies), with typical subophitic and/or microgranular textures. Different rock units from the mafic intrusion show gradational boundaries in between. They show some indications of low grade metamorphism, where primary minerals are transformed into secondary ones. Geochemically, the Shahira layered mafic intrusion is characterized by enrichment in LILE relative to HFSE (e.g. Nb, P, Zr, Ti, Y), and LREE relative to HREE [(La/Lu)n= 4.75–8.58], with subalkaline characters. It has geochemical characteristics of pre-collisional arc-type environment. The geochemical signature of the investigated gabbros indicates partial melting of mantle wedge in a volcanic-arc setting, being followed by fractional crystallization and crustal contamination. Fractional crystallization processes played a vital role during emplacement of the Shahira intrusion and evolution of its mafic and intermediate rock units. The initial magma was evolved through crystallization of hornblende which was caused by slight increasing of H2O in the magma after crystallization of liquidus olivine, pyroxene and Ca-rich plagioclase. The gabbroic rocks crystallized at pressures between 4.5 and 6.9kbar (~15–20km depth). Whereas, the diorites yielded the lowest crystallization pressure between 1.0 to 4.4Kbar (<10km depth). Temperature was estimated by several geothermometers, which yielded crystallization temperatures ranging from 835

Sill intrusion in volcanic calderas: implications for vent opening probability

Science.gov (United States)

Giudicepietro, Flora; Macedonio, Giovanni; Martini, Marcello; D'Auria, Luca

2017-04-01

Calderas show peculiar behaviors with remarkable dynamic processes, which do not often culminate in eruptions. Observations and studies conducted in recent decades have shown that the most common cause of unrest in the calderas is due to magma intrusion; in particular, the intrusion of sills at shallow depths. Monogenic cones, with large areal dispersion, are quite common in the calderas, suggesting that the susceptibility analysis based on geological features, is not strictly suitable for estimating the vent opening probability in calderas. In general, the opening of a new eruptive vent can be regarded as a rock failure process. The stress field in the rocks that surrounds and tops the magmatic reservoirs plays an important role in causing the rock failure and creating the path that magma can follow towards the surface. In this conceptual framework, we approach the problem of getting clues about the probability of vent opening in volcanic calderas through the study of the stress field produced by the intrusion of magma, in particular, by the intrusion of a sill. We simulate the intrusion of a sill free to expand radially, with shape and dimensions which vary with time. The intrusion process is controlled by the elastic response of the rock plate above the sill, which bends because of the intrusion, and by gravity, that drives the magma towards the zones where the thickness of the sill is smaller. We calculated the stress field in the plate rock above the sill. We found that at the bottom of the rock plate above the sill the maximum intensity of tensile stress is concentrated at the front of the sill and spreads radially with it, over time. For this reason, we think that the front of the spreading sill is prone to open for eruptive vents. Even in the central area of the sill the intensity of stress is relatively high, but at the base of the rock plate stress is compressive. Under isothermal conditions, the stress soon reaches its maximum value (time interval

Research on Abnormal Detection Based on Improved Combination of K - means and SVDD

Science.gov (United States)

Hao, Xiaohong; Zhang, Xiaofeng

2018-01-01

In order to improve the efficiency of network intrusion detection and reduce the false alarm rate, this paper proposes an anomaly detection algorithm based on improved K-means and SVDD. The algorithm first uses the improved K-means algorithm to cluster the training samples of each class, so that each class is independent and compact in class; Then, according to the training samples, the SVDD algorithm is used to construct the minimum superspheres. The subordinate relationship of the samples is determined by calculating the distance of the minimum superspheres constructed by SVDD. If the test sample is less than the center of the hypersphere, the test sample belongs to this class, otherwise it does not belong to this class, after several comparisons, the final test of the effective detection of the test sample.In this paper, we use KDD CUP99 data set to simulate the proposed anomaly detection algorithm. The results show that the algorithm has high detection rate and low false alarm rate, which is an effective network security protection method.

Trouble Brewing: Using Observations of Invariant Behavior to Detect Malicious Agency in Distributed Control Systems

Science.gov (United States)

McEvoy, Thomas Richard; Wolthusen, Stephen D.

Recent research on intrusion detection in supervisory data acquisition and control (SCADA) and DCS systems has focused on anomaly detection at protocol level based on the well-defined nature of traffic on such networks. Here, we consider attacks which compromise sensors or actuators (including physical manipulation), where intrusion may not be readily apparent as data and computational states can be controlled to give an appearance of normality, and sensor and control systems have limited accuracy. To counter these, we propose to consider indirect relations between sensor readings to detect such attacks through concurrent observations as determined by control laws and constraints.

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

Environmental Characteristics of Carbonatite and Alkaline Intrusion-related Rare Earth Element (REE) Deposits

Science.gov (United States)

Seal, R. R., II; Piatak, N. M.

2017-12-01

Carbonatites and alkaline intrusions are important sources of REEs. Environmental risks related to these deposit types have been assessed through literature review and evaluation of the geochemical properties of representative samples of mill tailings and their leachates. The main ore mineral in carbonatite deposits is bastnasite [(Ce,La)(CO3)F], which is found with dolomite and calcite ( 65 %), barite (20 - 25 %), plus a number of minor accessory minerals including sulfides such as galena and pyrite. Generally, alkaline intrusion-related REE deposits either occur in layered complexes or with dikes and veins cutting alkaline intrusions. Such intrusions have a more diverse group of REE ore minerals that include fluorcarbonates, oxides, silicates, and phosphates. Ore also can include minor calcite and iron (Fe), lead (Pb), and zinc (Zn) sulfides. The acid-generating potential of both deposit types is low because of a predominance of carbonate minerals in the carbonatite deposits, the presence of feldspars and minor calcite in alkaline intrusion-related deposits, and to only minor to trace occurrence of potentially acid-generating sulfide minerals. Both deposit types, however, are produced by igneous and hydrothermal processes that enrich high-field strength, incompatible elements, which typically are excluded from common rock-forming minerals. Elements such as yttrium (Y), niobium Nb), zirconium (Zr), hafnium (Hf), tungsten (W), titanium (Ti), tantalum (Ta), scandium (Sc), thorium (Th), and uranium (U) can be characteristic of these deposits and may be of environmental concern. Most of these elements, including the REEs, but with the exception of U, have low solubilities in water at the near-neutral pH values expected around these deposits. Mill tailings from carbonatite deposits can exceed residential soil and sediment criteria for Pb, and leachates from mill tailings can exceed drinking water guidelines for Pb. The greatest environmental challenges, however, are

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

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.

Host location by ichneumonid parasitoids is associated with nest dimensions of the host bee species.

Science.gov (United States)

Flores-Prado, L; Niemeyer, H M

2012-08-01

Parasitoid fitness depends on the ability of females to locate a host. In some species of Ichneumonoidea, female parasitoids detect potential hosts through vibratory cues emanating from them or through vibrational sounding produced by antennal tapping on the substrate. In this study, we (1) describe host location behaviors in Grotea gayi Spinola (Hymenoptera: Ichneumonidae) and Labena sp. on nests of Manuelia postica Spinola (Hymenoptera: Apidae), (2) compare nest dimensions between parasitized and unparasitized nests, (3) correlate the length of M. postica nests with the number of immature individuals developing, and (4) establish the relative proportion of parasitized nests along the breeding period of M. postica. Based on our results, we propose that these parasitoids use vibrational sounding as a host location mechanism and that they are able to assess host nest dimensions and choose those which may provide them with a higher fitness. Finally, we discuss an ancestral host-parasitoid relationship between Manuelia and ichneumonid species.

Adaptive intrusion data system

International Nuclear Information System (INIS)

Johnson, C.S.

1976-01-01

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

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

Multiple Resource Host Architecture (MRHA) for the Mobile Detection Assessment Response System (MDARS) Revision A

National Research Council Canada - National Science Library

Everett, H

2000-01-01

The Mobile Detection Assessment and Response System (MDARS) program employs multiple robotic security platforms operating under the high level control of a remote host, with the direct supervision of a human operator...

Trauma Films, Information Processing, and Intrusive Memory Development

Science.gov (United States)

Holmes, Emily A.; Brewin, Chris R.; Hennessy, Richard G.

2004-01-01

Three experiments indexed the effect of various concurrent tasks, while watching a traumatic film, on intrusive memory development. Hypotheses were based on the dual-representation theory of posttraumatic stress disorder (C. R. Brewin, T. Dalgleish, & S. Joseph, 1996). Nonclinical participants viewed a trauma film under various encoding conditions…

Coeval Formation of Zircon Megacrysts and Host Magmas in the Eifel Volcanic Field (Germany) Based on High Spatial Resolution Petrochronology

Science.gov (United States)

Schmitt, Axel; Klitzke, Malte; Gerdes, Axel; Ludwig, Thomas; Schäfer, Christof

2017-04-01

Zircon megacrysts (approx. 0.5-6 mm in diameter) from the Quaternary West and East Eifel volcanic fields, Germany, occur as euhedral crystals in porous K-spar rich plutonic ejecta clasts, and as partially resorbed xenocrysts in tephrite lava. Their relation to the host volcanic rocks has remained contentious because the dominantly basanitic to phonolitic magma compositions in the Eifel are typically zircon undersaturated. We carried out a detailed microanalytical study of zircon megacrysts from seven locations (Emmelberg and Rockeskyll in the West Eifel; Bellerberg, Laacher See, Mendig, Rieden, and Wehr in the East Eifel). Crystals were embedded in epoxy, sectioned to expose interiors through grinding with abrasives, diamond-polished, and mapped by optical microscopy, backscattered electron, and cathodoluminescence imaging. Subsequently, isotope-specific analysis using secondary ionization mass spectrometry (SIMS) and laser ablation inductively coupled mass spectrometry (LA-ICP-MS) was carried out placing 100 correlated spots on 20 selected crystals. Concordant U-Th disequilibrium and U-Pb ages determined by SIMS are between ca. 430 ka (Rieden) and 170 ka (Mendig) and indicate that the megacryst zircons crystallized almost always briefly before eruption. A significant gap between zircon megacryst crystallization (ca. 230 ka) and eruption (ca. 45 ka) ages was only detected for the Emmelberg location. SIMS trace element abundances (e.g., rare earth elements) vary by orders-of-magnitude and correlate with domain boundaries visible in cathodoluminescence; trace element patterns match those reported for zircon from syenitic origins. Isotopic compositions are homogeneous within individual crystals, but show some heterogeneity between different crystals from the same locality. Average isotopic values (δ18O SMOW = +5.3±0.6 ‰ by SIMS; present-day ɛHf = +1.7±2.5 ‰ by LA-ICP-MS; 1 standard deviation), however, are consistent with source magmas being dominantly mantle

Intrusion detection for IP-based multimedia communications over wireless networks

CERN Document Server

Tang, Jin

2013-01-01

IP-based multimedia communications have become increasingly popular in recent years. With the increasing coverage of the IEEE 802:11™ based wireless networks, IP-based multimedia communications over wireless networks are also drawing extensive attention in both academia and industry. Due to the openness and distributed nature of the protocols involved, such as the session initiation protocol (SIP) and the IEEE 802:11™ standard, it becomes easy for malicious users in the network to achieve their own gain or disrupt the service by deviating from the normal protocol behaviors. This SpringerBrief

Time to face it! Facebook intrusion and the implications for romantic jealousy and relationship satisfaction.

Science.gov (United States)

Elphinston, Rachel A; Noller, Patricia

2011-11-01

Young people's exposure to social network sites such as Facebook is increasing, along with the potential for such use to complicate romantic relationships. Yet, little is known about the overlaps between the online and offline worlds. We extended previous research by investigating the links between Facebook intrusion, jealousy in romantic relationships, and relationship outcomes in a sample of undergraduates currently in a romantic relationship. A Facebook Intrusion Questionnaire was developed based on key features of technological (behavioral) addictions. An eight-item Facebook Intrusion Questionnaire with a single-factor structure was supported; internal consistency was high. Facebook intrusion was linked to relationship dissatisfaction, via jealous cognitions and surveillance behaviors. The results highlight the possibility of high levels of Facebook intrusion spilling over into romantic relationships, resulting in problems such as jealousy and dissatisfaction. The results have implications for romantic relationships and for Facebook users in general.

Non-invasive and non-intrusive gas flow measurement based on the dynamic thermal characteristics of a pipeline

Science.gov (United States)

Fan, Zichuan; Cai, Maolin; Xu, Weiqing

2012-10-01

This paper proposes a non-intrusive and non-invasive method for measuring the gas flow rate in pneumatic industry. A heater unit is fixed on the partial circumference of the external wall of a pipeline and emits specific thermal pulses in a predetermined mode. Two sensors attached to the external wall detect the upstream temperature, and the gas flow can be measured according to the relationship between the flow rate and the dynamic thermal characteristics of the pipeline. To determine the preferable relationship, the temperature field model of the measurement system is built. Then, based on the measurement modes and the corresponding simulations, the objective functions for the gas flow specified on different dynamic thermal characteristics are established. Additionally, the minimum measurement time of the method, named reference time scale, is proposed. Further, robustness tests of the measurement method are derived by considering the influences of multiple factors on the objective functions. The experiments confirm that this method does not need to open the pipeline and disturb the flow regime in order to obtain the data; this method also avoids the typical time-consuming and complex operations, resists ambient temperature disturbance and achieves approximately acceptable results.

Non-invasive and non-intrusive gas flow measurement based on the dynamic thermal characteristics of a pipeline

International Nuclear Information System (INIS)

Fan, Zichuan; Cai, Maolin; Xu, Weiqing

2012-01-01

This paper proposes a non-intrusive and non-invasive method for measuring the gas flow rate in pneumatic industry. A heater unit is fixed on the partial circumference of the external wall of a pipeline and emits specific thermal pulses in a predetermined mode. Two sensors attached to the external wall detect the upstream temperature, and the gas flow can be measured according to the relationship between the flow rate and the dynamic thermal characteristics of the pipeline. To determine the preferable relationship, the temperature field model of the measurement system is built. Then, based on the measurement modes and the corresponding simulations, the objective functions for the gas flow specified on different dynamic thermal characteristics are established. Additionally, the minimum measurement time of the method, named reference time scale, is proposed. Further, robustness tests of the measurement method are derived by considering the influences of multiple factors on the objective functions. The experiments confirm that this method does not need to open the pipeline and disturb the flow regime in order to obtain the data; this method also avoids the typical time-consuming and complex operations, resists ambient temperature disturbance and achieves approximately acceptable results. (paper)

Identification of host response signatures of infection.

Energy Technology Data Exchange (ETDEWEB)

Branda, Steven S.; Sinha, Anupama; Bent, Zachary

2013-02-01

Biological weapons of mass destruction and emerging infectious diseases represent a serious and growing threat to our national security. Effective response to a bioattack or disease outbreak critically depends upon efficient and reliable distinguishing between infected vs healthy individuals, to enable rational use of scarce, invasive, and/or costly countermeasures (diagnostics, therapies, quarantine). Screening based on direct detection of the causative pathogen can be problematic, because culture- and probe-based assays are confounded by unanticipated pathogens (e.g., deeply diverged, engineered), and readily-accessible specimens (e.g., blood) often contain little or no pathogen, particularly at pre-symptomatic stages of disease. Thus, in addition to the pathogen itself, one would like to detect infection-specific host response signatures in the specimen, preferably ones comprised of nucleic acids (NA), which can be recovered and amplified from tiny specimens (e.g., fingerstick draws). Proof-of-concept studies have not been definitive, however, largely due to use of sub-optimal sample preparation and detection technologies. For purposes of pathogen detection, Sandia has developed novel molecular biology methods that enable selective isolation of NA unique to, or shared between, complex samples, followed by identification and quantitation via Second Generation Sequencing (SGS). The central hypothesis of the current study is that variations on this approach will support efficient identification and verification of NA-based host response signatures of infectious disease. To test this hypothesis, we re-engineered Sandia's sophisticated sample preparation pipelines, and developed new SGS data analysis tools and strategies, in order to pioneer use of SGS for identification of host NA correlating with infection. Proof-of-concept studies were carried out using specimens drawn from pathogen-infected non-human primates (NHP). This work provides a strong foundation for

Non-intrusive Assessment of Photosystem II and Photosystem I in Whole Coral Tissues

Directory of Open Access Journals (Sweden)

Milán Szabó

2017-08-01

Full Text Available Reef building corals (phylum Cnidaria harbor endosymbiotic dinoflagellate algae (genus Symbiodinium that generate photosynthetic products to fuel their host's metabolism. Non-invasive techniques such as chlorophyll (Chl fluorescence analyses of Photosystem II (PSII have been widely used to estimate the photosynthetic performance of Symbiodinium in hospite. However, since the spatial origin of PSII chlorophyll fluorescence in coral tissues is uncertain, such signals give limited information on depth-integrated photosynthetic performance of the whole tissue. In contrast, detection of absorbance changes in the near infrared (NIR region integrates signals from deeper tissue layers due to weak absorption and multiple scattering of NIR light. While extensively utilized in higher plants, NIR bio-optical techniques are seldom applied to corals. We have developed a non-intrusive measurement method to examine photochemistry of intact corals, based on redox kinetics of the primary electron donor in Photosystem I (P700 and chlorophyll fluorescence kinetics (Fast-Repetition Rate fluorometry, FRRf. Since the redox state of P700 depends on the operation of both PSI and PSII, important information can be obtained on the PSII-PSI intersystem electron transfer kinetics. Under moderate, sub-lethal heat stress treatments (33°C for ~20 min, the coral Pavona decussata exhibited down-regulation of PSII electron transfer kinetics, indicated by slower rates of electron transport from QA to plastoquinone (PQ pool, and smaller relative size of oxidized PQ with concomitant decrease of a specifically-defined P700 kinetics area, which represents the active pool of PSII. The maximum quantum efficiency of PSII (Fv/Fm and functional absorption cross-section of PSII (σPSII remained unchanged. Based on the coordinated response of P700 parameters and PSII-PSI electron transport properties, we propose that simple P700 kinetics parameters as employed here serve as indicators of

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