Show simple item record

dc.contributor.authorAbouzakhar, N.S.
dc.contributor.authorChen, H.
dc.contributor.authorChristianson, B.
dc.date.accessioned2011-11-02T16:01:08Z
dc.date.available2011-11-02T16:01:08Z
dc.date.issued2011-04-01
dc.identifier.citationAbouzakhar , N S , Chen , H & Christianson , B 2011 , ' An enhanced fuzzy ARM approach for intrusion detection ' , International Journal of Digital Crime and Forensics , vol. 3 , no. 2 , pp. 41-61 . https://doi.org/10.4018/jdcf.2011040104
dc.identifier.issn1941-6210
dc.identifier.otherPURE: 439172
dc.identifier.otherPURE UUID: e1d3770d-7839-49eb-b770-3f56d9dbb707
dc.identifier.otherScopus: 80053007307
dc.identifier.urihttp://hdl.handle.net/2299/6889
dc.descriptionOriginal article can be found at: http://www.igi-global.com/ Copyright IGI Global [Full text of this article is not available in the UHRA]
dc.description.abstractThe integration of fuzzy logic with data mining methods such as association rules has achieved interesting results in various digital forensics applications. As a data mining technique, the association rule mining (ARM) algorithm uses ranges to convert any quantitative features into categorical ones. Such features lead to the sudden boundary problem, which can be smoothed by incorporating fuzzy logic so as to develop interesting patterns for intrusion detection. This paper introduces a Fuzzy ARM-based intrusion detection model that is tested on the CAIDA 2007 backscatter network traffic dataset. Moreover, the authors present an improved algorithm named Matrix Fuzzy ARM algorithm for mining fuzzy association rules. The experiments and results that are presented in this paper demonstrate the effectiveness of integrating fuzzy logic with association rule mining in intrusion detection. The performance of the developed detection model is improved by using this integrated approach and improved algorithm.en
dc.format.extent21
dc.language.isoeng
dc.relation.ispartofInternational Journal of Digital Crime and Forensics
dc.subjectalgorithms
dc.subjectcybercrime detection
dc.subjectforensic computing
dc.subjectintrusion detection
dc.subjectmatrix fuzzy ARM
dc.titleAn enhanced fuzzy ARM approach for intrusion detectionen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=80053007307&partnerID=8YFLogxK
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.4018/jdcf.2011040104
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record