Statistical model applied to NetFlow for network intrusion detection

被引：3

作者：

Proto A. ^{[1
]}

Alexandre L.A. ^{[1
]}

Batista M.L. ^{[1
]}

Oliveira I.L. ^{[1
]}

Cansian A.M. ^{[1
]}

机构：

[1] UNESP - Universidade Estadual Paulista 'Júlio de Mesquita Filho', Departamento de Ciências de Computação e Estatística, ACME Computer Security Research Lab., 2265, Jd. Nazareth, S. J. do Rio Preto, S. Paulo, Cristóvão Colombo Street

来源：

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 2010年 / 6480卷 / PART 2期

关键词：

anomaly; intrusion detection; NetFlow; network; Security; statistical;

D O I：

10.1007/978-3-642-17697-5_9

中图分类号：

学科分类号：

摘要：

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.

引用

页码：179 / 191

页数：12

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