Title :
A study on cost-effective P2P traffic classification
Author :
Ban, Tao ; Guo, Shanqing ; Eto, Masashi ; Inoue, Daisuke ; Nakao, Koji
Author_Institution :
Nat. Inst. of Inf. & Commun. Technol., Tokyo, Japan
Abstract :
Characterization of Peer-to-Peer (P2P) traffic is an essential step to develop workload models towards capacity planning and cyber-threat countermeasure over P2P networks. In this paper, we present a new scheme for characterizing P2P file sharing hosts based on transport layer statistical features. The proposed scheme is featured by its tunability over monitoring cost, system response time, and prediction accuracy. We further employ feature selection to identify the most essential discriminators for the analysis. Experimental results show that an equally accurate system could be obtained using only 3 out of the 18 defined discriminators, which further enhances the adaptability and reduces the monitoring cost of the system.
Keywords :
Internet; computer network security; pattern classification; peer-to-peer computing; statistical analysis; telecommunication network planning; telecommunication traffic; Internet communications; P2P file sharing host characterization; P2P networks; capacity planning; cost-effective P2P traffic classification; cyber-threat countermeasure; feature selection; monitoring cost reduction; prediction accuracy; statistical studies; system response time; transport layer statistical features; workload models; Accuracy; Entropy; IP networks; Monitoring; Protocols; Support vector machines; Vectors;
Conference_Titel :
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1488-6
Electronic_ISBN :
2161-4393
DOI :
10.1109/IJCNN.2012.6252672
