Using Statistical Discriminators and Cluster Analysis to P2P and Attack Traffic Monitoring

Author

do Carmo, M.F.F. ; Junior, G.P.S. ; Maia, J.E.B. ; Holanda, Raimir

Author_Institution

Univ. of Fortaleza, Fortaleza

fYear

2007

fDate

10-12 Sept. 2007

Firstpage

67

Lastpage

75

Abstract

In the last few years, we have seen that the attack and P2P traffic has increased significantly. Currently, P2P traffic represents a significant portion of Internet traffic and the attacks represent a serious threat to computer systems. The approach presented here uses a small number of statistical discriminators and cluster analysis to identify such kind of traffics, obtaining results that are better than the results found into previous papers. We perform an empirical test using real traces.

Keywords

Internet; discriminators; pattern classification; peer-to-peer computing; Internet traffic; P2P; attack traffic monitoring; cluster analysis; pattern classification; statistical discriminators; Application software; Communication system traffic control; Computer network management; Computer science; Computerized monitoring; Internet; Machine learning; Performance evaluation; Statistical analysis; Telecommunication traffic; attack traffic identification; p2p traffic identification; pattern classification; statistical discriminators;

fLanguage

English

Publisher

ieee

Conference_Titel

Network Operations and Management Symposium, 2007. LANOMS 2007. Latin American

Conference_Location

Rio de Janeiro

Print_ISBN

978-1-4244-1182-5

Electronic_ISBN

978-1-4244-1182-5

Type

conf

DOI

10.1109/LANOMS.2007.4362461

Filename

4362461