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dc.contributor.authorAbouzakhar, Nasser
dc.contributor.authorManson, Gordon
dc.date.accessioned2014-05-28T09:00:24Z
dc.date.available2014-05-28T09:00:24Z
dc.date.issued2004
dc.identifier.citationAbouzakhar , N & Manson , G 2004 , ' Evaluation of Intelligent Intrusion Detection Models ' , International Journal of Digital Evidence , vol. 3 , no. 1 .
dc.identifier.urihttp://hdl.handle.net/2299/13551
dc.description.abstractThis paper discusses an evaluation methodology that can be used to assess the performance of intelligent techniques at detecting, as well as predicting, unauthorised activities in networks. The effectiveness and the performance of any developed intrusion detection model will be determined by means of evaluation and validation. The evaluation and the learning prediction performance for this task will be discussed, together with a description of validation procedures. The performance of developed detection models that incorporate intelligent elements can be evaluated using well known standard methods, such as matrix confusion, ROC curves and Lift charts. In this paper these methods, as well as other useful evaluation approaches, are discussed.en
dc.format.extent20
dc.format.extent455765
dc.language.isoeng
dc.relation.ispartofInternational Journal of Digital Evidence
dc.subjectPrediction performance
dc.subjectIntrusion detection
dc.subjectEvaluation
dc.titleEvaluation of Intelligent Intrusion Detection Modelsen
dc.contributor.institutionSchool of Computer Science
dc.description.statusPeer reviewed
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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