Substantiating Anomalies In Wireless Networks Using Group Outlier Scores

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Title Substantiating Anomalies In Wireless Networks Using Group Outlier Scores
Author Sithirasenan, Elankayer; Muthukkumarasamy, Vallipuram
Journal Name Journal of Software
Editor Jameela Al-Jaroodi and Nader Mohamed
Year Published 2011
Place of publication Finland
Publisher Academy Publisher
Abstract Huge amounts of network traces can be collected from today’s busy computer networks. Analyzing these traces could pave the way to detect unusual conditions and/or other anomalies. Presently, due to the lack of effective substantiating mechanisms intrusion detection systems often exhibit numerous false positives or negatives. The efficiency of a network intrusion detection system (NIDS) depends very much on detecting and effectively validating the detected anomalies. Furthermore, most NIDSs do not have proven mechanisms that will easily accommodate legitimate dynamic changes. Achieving dynamic adaptation in real time has been a long standing desire for effective intrusion detection and prevention. Real time detection of outliers is a feasible option to substantiate anomalies in large data sets, leading to effective intrusion detection and prevention. In this context we propose and investigate a novel mechanism to detect intruders and to classify security threats using group outliers. Our system monitors for timing and/or behavioral anomalies and uses outlier based techniques to substantiate the anomaly. In this paper we introduce the concept of Group Outlier Score (GOS) and its use in substantiating security threats in wireless networks. We have tested the concept on our experimental wireless networking environment. The analysis of the results reveals that with a threshold value of 1.2 for GOS our system demonstrates optimum performance.
Peer Reviewed Yes
Published Yes
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Copyright Statement Copyright [year] Academy Publisher. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
Volume 6
Issue Number 4
Page from 678
Page to 689
ISSN 1796-217X
Date Accessioned 2012-02-06; 2012-02-17T05:11:15Z
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Information and Computing Sciences
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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