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Intrusion Detection System Based On Flows Using Machine Learning Algorithms

dc.contributor.authorKakihata, E. M.
dc.contributor.authorSapia, H. M.
dc.contributor.authorOikawa, R. T.
dc.contributor.authorPereira, D. R.
dc.contributor.authorPapa, J. P. [UNESP]
dc.contributor.authorAlburquerque, V. H. C.
dc.contributor.authorSilva, F. A.
dc.contributor.institutionUniv Oeste Paulista Unoeste
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniv Fortaleza Unifor
dc.date.accessioned2018-11-26T17:41:53Z
dc.date.available2018-11-26T17:41:53Z
dc.date.issued2017-10-01
dc.description.abstractThe use of technology by different types of devices generates a large flow of confidential and personal information. Referencing this situation, it is necessary to use computer security tools, such as Intrusion Detection Systems (IDS). This work presents an IDS that can perform the flow-based analysis (netflow). The first step of this research conducted an analysis on flows previously collected and properly detected three different types of attacks. In the second step, the flows were organized to be used in machine learning algorithms.en
dc.description.affiliationUniv Oeste Paulista Unoeste, Presidente Prudente, SP, Brazil
dc.description.affiliationUniv Estadual Paulista, UNESP, Comp Sci Dept, Bauru, SP, Brazil
dc.description.affiliationUniv Fortaleza Unifor, Appl Informat Grad Program, Fortaleza, Ceara, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, UNESP, Comp Sci Dept, Bauru, SP, Brazil
dc.format.extent1988-1993
dc.identifier.citationIeee Latin America Transactions. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 15, n. 10, p. 1988-1993, 2017.
dc.identifier.fileWOS000413336000025.pdf
dc.identifier.issn1548-0992
dc.identifier.urihttp://hdl.handle.net/11449/163405
dc.identifier.wosWOS:000413336000025
dc.language.isopor
dc.publisherIeee-inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Latin America Transactions
dc.relation.ispartofsjr0,253
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectintrusion detection system
dc.subjectnetflow
dc.subjectmachine learning
dc.titleIntrusion Detection System Based On Flows Using Machine Learning Algorithmsen
dc.typeArtigo
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee-inst Electrical Electronics Engineers Inc
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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