05845307

a

05845307 Dozono, Hiroshi Nakakuni, Masanori Kabashima, Takaru Hara, Shigeomi Analysis of packet traffics and detection of abnormal traffics using Pareto learning self organizing maps. Wong, Kok Wai (ed.) et al., Neural information processing. Models and applications. 17th international conference, ICONIP 2010, Sydney, Australia, November 22--25, 2010. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-17533-6/pbk). Lecture Notes in Computer Science 6444, 329-336 (2010). 2010 Berlin: Springer EN

doi:10.1007/978-3-642-17534-3_40

Summary: Recently, the spread of the Internet makes familiar to the incident concerning the Internet, such as a DoS attack and a DDoS attack. Some methods which detect the abnormal traffics in the network using the information from headers and payloads of IP-packets transmitted in the networks are proposed. In this research, we propose a method of Pareto Learning SOM (Self Organizing Map) for IP packet flow analysis in which the occurrence rate is used for SOM computing. The flow of the packets can be visualized on the map and it can be used for detecting the abnormal flows of packets.