Comparative evaluation of different classification techniques for masquerade attack detection

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dc.contributor.authorElmasry, W.
dc.contributor.authorAkbulut, A.
dc.contributor.authorZaim, Abdül Halim
dc.date.accessioned2021-01-25T21:48:04Z
dc.date.available2021-01-25T21:48:04Z
dc.date.issued2020
dc.departmentİstanbul Ticaret Üniversitesien_US
dc.description.abstractMasquerade detection is a special type of intrusion detection problem. Effective and early intrusion detection is a crucial basis for computer security. Although of considerable work has been focused on masquerade detection for more than a decade, achieving a high level of accuracy and a comparatively low degree of false alarm rate is still a big challenge. In this paper, we present an extensive empirical study in the area of user behaviour profiling-based masquerade detection using six of different existed machine learning methods in Azure Machine Learning (AML) studio. In order to surpass previous studies on this subject, we used four free and publicly available datasets with seven data configurations are implemented from them. Moreover, eight well-known masquerade detection evaluation metrics are used to assess methods performance against each data configuration. Finally, intensive quantitative and ROC curves analyses of results are provided at the end of this paper. Copyright © 2020 Inderscience Enterprises Ltd.en_US
dc.identifier.doi10.1504/IJICS.2020.108848en_US
dc.identifier.endpage209en_US
dc.identifier.issn1744-1765
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85092017179en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage187en_US
dc.identifier.urihttps://doi.org/10.1504/IJICS.2020.108848
dc.identifier.urihttps://hdl.handle.net/11467/4503
dc.identifier.volume13en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInderscience Enterprises Ltd.en_US
dc.relation.ispartofInternational Journal of Information and Computer Securityen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAnomaly-based detectionen_US
dc.subjectComputer securityen_US
dc.subjectIntrusion detectionen_US
dc.subjectMachine learningen_US
dc.subjectMasquerade detectionen_US
dc.titleComparative evaluation of different classification techniques for masquerade attack detectionen_US
dc.typeArticleen_US

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