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dc.contributor.authorSithirasenan, Elankayeren_US
dc.contributor.authorMuthukkumarasamy, Vallipuramen_US
dc.contributor.editorJameela Al-Jaroodi and Nader Mohameden_US
dc.date.accessioned2012-02-06en_US
dc.date.accessioned2012-02-17T05:11:15Z
dc.date.accessioned2017-03-01T23:20:15Z
dc.date.available2017-03-01T23:20:15Z
dc.date.issued2011en_US
dc.date.modified2012-02-17T05:11:15Z
dc.identifier.issn1796-217Xen_US
dc.identifier.doi10.4304/jsw.6.4.678-689en_US
dc.identifier.urihttp://hdl.handle.net/10072/42913
dc.description.abstractHuge 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.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.format.extent180365 bytes
dc.format.mimetypeapplication/pdf
dc.publisherAcademy Publisheren_US
dc.publisher.placeFinlanden_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom678en_US
dc.relation.ispartofpageto689en_US
dc.relation.ispartofissue4en_US
dc.relation.ispartofjournalJournal of Softwareen_US
dc.relation.ispartofvolume6en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchInformation and Computing Sciencesen_US
dc.subject.fieldofresearchcode089999en_US
dc.titleSubstantiating Anomalies In Wireless Networks Using Group Outlier Scoresen_US
dc.typeJournal article
dc.type.descriptionJournal Articles (Refereed Article)en_US
dc.type.codec1en_US
gro.facultyFaculty of Science, Environment, Engineering and Technologyen_US
gro.rights.copyrightCopyright [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.en_US
gro.date.issued2011
gro.hasfulltextFull Text


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