Intrusion detection in computer networks using optimum-path forest clustering

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dc.contributor.authorCosta, Kelton [UNESP]
dc.contributor.authorPereira, Clayton [UNESP]
dc.contributor.authorNakamura, Rodrigo [UNESP]
dc.contributor.authorPapa, Joao [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:27:18Z
dc.date.available2014-05-27T11:27:18Z
dc.date.issued2012-12-01
dc.description.abstractNowadays, organizations face the problem of keeping their information protected, available and trustworthy. In this context, machine learning techniques have also been extensively applied to this task. Since manual labeling is very expensive, several works attempt to handle intrusion detection with traditional clustering algorithms. In this paper, we introduce a new pattern recognition technique called Optimum-Path Forest (OPF) clustering to this task. Experiments on three public datasets have showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, since it outperformed some state-of-the-art unsupervised techniques. © 2012 IEEE.en
dc.description.affiliationDepartment of Computing Universidade Estadual Paulista (UNESP)
dc.description.affiliationUnespDepartment of Computing Universidade Estadual Paulista (UNESP)
dc.format.extent128-131
dc.identifierhttp://dx.doi.org/10.1109/LCN.2012.6423588
dc.identifier.citationProceedings - Conference on Local Computer Networks, LCN, p. 128-131.
dc.identifier.doi10.1109/LCN.2012.6423588
dc.identifier.scopus2-s2.0-84874287364
dc.identifier.urihttp://hdl.handle.net/11449/73827
dc.identifier.wosWOS:000316963600016
dc.language.isoeng
dc.relation.ispartofProceedings - Conference on Local Computer Networks, LCN
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectMachine learning techniques
dc.subjectManual labeling
dc.subjectOptimum-path forests
dc.subjectPattern recognition techniques
dc.subjectTraditional clustering
dc.subjectUnsupervised techniques
dc.subjectForestry
dc.subjectIntrusion detection
dc.subjectLearning systems
dc.subjectPattern recognition
dc.subjectClustering algorithms
dc.subjectAlgorithms
dc.subjectData
dc.subjectNetworks
dc.subjectSet
dc.titleIntrusion detection in computer networks using optimum-path forest clusteringen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
unesp.author.orcid0000-0002-6494-7514[4]
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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