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dc.contributor.authorPadmasiri, MAT
dc.contributor.authorGanepola, VVV
dc.contributor.authorHerath, RKHMSD
dc.contributor.authorWelagedara, LP
dc.contributor.authorGanepola, GANS
dc.contributor.authorVekneswaran, P
dc.date.accessioned2020-12-31T23:13:07Z
dc.date.available2020-12-31T23:13:07Z
dc.date.issued2020
dc.identifier.urihttp://ir.kdu.ac.lk/handle/345/3036
dc.description.abstractWhere world is moving towards digitalization, it is crucial that network intrusions detection and prevention is addresses in ordered to create a secured network. This paper covers why deep learning was considered and what are the deep learning approaches for network intrusion detection. For each approach the challenges, missed elements and the unique features that are found in current domain state are also highlighted. As a conclusion this paper highlights why CNN and LSTM would be successful approach for intrusion detection and why in the current domain context it is required to create scalable solution with both intrusion detection and prevention involved.en_US
dc.language.isoenen_US
dc.subjectNetwork Intrusion Detection and Prevention Systemen_US
dc.subjectDeep Learningen_US
dc.subjectNSLKDDen_US
dc.titleSurvey on Deep learning based Network Intrusion Detection and Prevention Systemsen_US
dc.typeArticle Full Texten_US
dc.identifier.journal13th International Research Conference General Sir John Kotelawala Defence Universityen_US
dc.identifier.pgnos427-436en_US


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