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Visualization of abnormal behavior detection using parallel coordinate and correspondence analysis

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dc.contributor.authorCho, J.-
dc.contributor.authorChoi, K.-
dc.contributor.authorShon, T.-
dc.contributor.authorMoon, J.-
dc.date.accessioned2021-09-06T09:53:41Z-
dc.date.available2021-09-06T09:53:41Z-
dc.date.created2021-06-17-
dc.date.issued2013-
dc.identifier.issn1343-4500-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/105938-
dc.description.abstractMost of the network management part, especially a network security needs effective visualization methods for flooding connections. Because many web systems using huge users are suffering from huge normal connections with flooding attacks. Also, most of the connection cases have to be monitored for intrusion detection including any kinds of abnormal connection cases. Therefore, in this paper we propose an effective visualization method with a classification method for classifying between normal and abnormal flooding network status.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherInternational Information Institute Ltd.-
dc.titleVisualization of abnormal behavior detection using parallel coordinate and correspondence analysis-
dc.typeArticle-
dc.contributor.affiliatedAuthorMoon, J.-
dc.identifier.scopusid2-s2.0-84877303799-
dc.identifier.bibliographicCitationInformation (Japan), v.16, no.3 A, pp.1847 - 1859-
dc.relation.isPartOfInformation (Japan)-
dc.citation.titleInformation (Japan)-
dc.citation.volume16-
dc.citation.number3 A-
dc.citation.startPage1847-
dc.citation.endPage1859-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorCategorical data classification-
dc.subject.keywordAuthorIntrusion detection-
dc.subject.keywordAuthorIntrusion visualization-
dc.subject.keywordAuthorNetwork monitoring-
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