Artículos de revistas
Statistical model applied to NetFlow for network intrusion detection
Fecha
2010-12-31Registro en:
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.
0302-9743
1611-3349
10.1007/978-3-642-17697-5_9
2-s2.0-78650597637
0095921943345974
0000-0003-4494-1454
Autor
Universidade Estadual Paulista (Unesp)
Institución
Resumen
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.