Statistical model applied to NetFlow for network intrusion detection

dc.contributor.authorProto, André [UNESP]
dc.contributor.authorAlexandre, Leandro A. [UNESP]
dc.contributor.authorBatista, Maira L. [UNESP]
dc.contributor.authorOliveira, Isabela L. [UNESP]
dc.contributor.authorCansian, Adriano M. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:25:26Z
dc.date.available2014-05-27T11:25:26Z
dc.date.issued2010-12-31
dc.description.abstractThe computers and network services became presence guaranteed in several places. These characteristics resulted in the growth of illicit events and therefore the computers and networks security has become an essential point in any computing environment. Many methodologies were created to identify these events; however, with increasing of users and services on the Internet, many difficulties are found in trying to monitor a large network environment. This paper proposes a methodology for events detection in large-scale networks. The proposal approaches the anomaly detection using the NetFlow protocol, statistical methods and monitoring the environment in a best time for the application. © 2010 Springer-Verlag Berlin Heidelberg.en
dc.description.affiliationUNESP - Universidade Estadual Paulista 'Júlio de Mesquita Filho' Departamento de Ciências de Computação e Estatística ACME Computer Security Research Lab., Cristóvão Colombo Street, 2265, Jd. Nazareth, S. J. do Rio Preto, S. Paulo
dc.description.affiliationUnespUNESP - Universidade Estadual Paulista 'Júlio de Mesquita Filho' Departamento de Ciências de Computação e Estatística ACME Computer Security Research Lab., Cristóvão Colombo Street, 2265, Jd. Nazareth, S. J. do Rio Preto, S. Paulo
dc.format.extent179-191
dc.identifierhttp://dx.doi.org/10.1007/978-3-642-17697-5_9
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 6480, n. PART 2, p. 179-191, 2010.
dc.identifier.doi10.1007/978-3-642-17697-5_9
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.lattes0095921943345974
dc.identifier.orcid0000-0003-4494-1454
dc.identifier.scopus2-s2.0-78650597637
dc.identifier.urihttp://hdl.handle.net/11449/72241
dc.language.isoeng
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.ispartofsjr0,295
dc.rights.accessRightsAcesso restrito
dc.sourceScopus
dc.subjectanomaly
dc.subjectintrusion detection
dc.subjectNetFlow
dc.subjectnetwork
dc.subjectSecurity
dc.subjectstatistical
dc.subjectNetFlows
dc.subjectInternet protocols
dc.subjectNetwork security
dc.subjectIntrusion detection
dc.titleStatistical model applied to NetFlow for network intrusion detectionen
dc.typeArtigo
dcterms.licensehttp://www.springer.com/open+access/authors+rights
unesp.author.lattes0095921943345974[5]
unesp.author.orcid0000-0003-4494-1454[5]
unesp.campusUniversidade Estadual Paulista (Unesp), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt

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