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http://acervodigital.unesp.br/handle/11449/72241
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DC Field | Value | Language |
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dc.contributor.author | Proto, André | - |
dc.contributor.author | Alexandre, Leandro A. | - |
dc.contributor.author | Batista, Maira L. | - |
dc.contributor.author | Oliveira, Isabela L. | - |
dc.contributor.author | Cansian, Adriano M. | - |
dc.date.accessioned | 2014-05-27T11:25:26Z | - |
dc.date.accessioned | 2016-10-25T18:33:26Z | - |
dc.date.available | 2014-05-27T11:25:26Z | - |
dc.date.available | 2016-10-25T18:33:26Z | - |
dc.date.issued | 2010-12-31 | - |
dc.identifier | http://dx.doi.org/10.1007/978-3-642-17697-5_9 | - |
dc.identifier.citation | Lecture 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.issn | 0302-9743 | - |
dc.identifier.issn | 1611-3349 | - |
dc.identifier.uri | http://hdl.handle.net/11449/72241 | - |
dc.identifier.uri | http://acervodigital.unesp.br/handle/11449/72241 | - |
dc.description.abstract | The 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.extent | 179-191 | - |
dc.language.iso | eng | - |
dc.source | Scopus | - |
dc.subject | anomaly | - |
dc.subject | intrusion detection | - |
dc.subject | NetFlow | - |
dc.subject | network | - |
dc.subject | Security | - |
dc.subject | statistical | - |
dc.subject | NetFlows | - |
dc.subject | Internet protocols | - |
dc.subject | Network security | - |
dc.subject | Intrusion detection | - |
dc.title | Statistical model applied to NetFlow for network intrusion detection | en |
dc.type | outro | - |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | - |
dc.description.affiliation | UNESP - 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.affiliationUnesp | UNESP - 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.doi | 10.1007/978-3-642-17697-5_9 | - |
dc.rights.accessRights | Acesso restrito | - |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.identifier.scopus | 2-s2.0-78650597637 | - |
Appears in Collections: | Artigos, TCCs, Teses e Dissertações da Unesp |
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