You are in the accessibility menu

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72241
Full metadata record
DC FieldValueLanguage
dc.contributor.authorProto, André-
dc.contributor.authorAlexandre, Leandro A.-
dc.contributor.authorBatista, Maira L.-
dc.contributor.authorOliveira, Isabela L.-
dc.contributor.authorCansian, Adriano M.-
dc.date.accessioned2014-05-27T11:25:26Z-
dc.date.accessioned2016-10-25T18:33:26Z-
dc.date.available2014-05-27T11:25:26Z-
dc.date.available2016-10-25T18:33:26Z-
dc.date.issued2010-12-31-
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.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttp://hdl.handle.net/11449/72241-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72241-
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.format.extent179-191-
dc.language.isoeng-
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.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
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.identifier.doi10.1007/978-3-642-17697-5_9-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.identifier.scopus2-s2.0-78650597637-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

There are no files associated with this item.
 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.