DocumentCode :
1882615
Title :
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
Link To Document :
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