Publication:

Machine Learning for Misuse-Based Network Intrusion Detection: Overview, Unified Evaluation and Feature Choice Comparison Framework

Date

2021
Journal article
https://doi.org/10.1109/ACCESS.2021.3075066
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dc.contributor.authorLe Jeune, Laurens
dc.contributor.authorGoedeme, Toon
dc.contributor.authorMentens, Nele
dc.contributor.imecauthorMentens, Nele
dc.contributor.orcidextGoedeme, Toon::0000-0002-7477-8961
dc.contributor.orcidimecLe Jeune, Laurens::0000-0003-0744-4897
dc.contributor.orcidimecMentens, Nele::0000-0001-8753-7895
dc.date.accessioned2022-02-24T09:36:46Z
dc.date.available2022-02-24T09:36:46Z
dc.date.issued2021
dc.identifier.doi10.1109/ACCESS.2021.3075066
dc.identifier.issn2169-3536
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/39093
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.source.beginpage63995
dc.source.endpage64015
dc.source.issuena
dc.source.journalIEEE ACCESS
dc.source.numberofpages21
dc.source.volume9
dc.subject.keywordsDATA SET
dc.subject.keywordsSYSTEM
dc.subject.keywordsALGORITHM
dc.subject.keywordsPERFORMANCE
dc.subject.keywordsINTERNET
dc.subject.keywordsSVM
dc.title

Machine Learning for Misuse-Based Network Intrusion Detection: Overview, Unified Evaluation and Feature Choice Comparison Framework

dc.typeJournal article
dspace.entity.typePublication
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