A study on cost-effective P2P traffic classification

IJCNN(2012)

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摘要
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.
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关键词
cyber-threat countermeasure,prediction accuracy,transport layer statistical features,statistical analysis,pattern classification,computer network security,p2p file sharing host characterization,internet communications,workload models,statistical studies,internet,telecommunication network planning,system response time,telecommunication traffic,peer-to-peer computing,feature selection,cost-effective p2p traffic classification,p2p networks,capacity planning,monitoring cost reduction,protocols,entropy,accuracy,support vector machines,vectors
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