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This paper focuses on the sampling-based Deep Packet Inspection for the traffic of P2P file sharing systems, especially for BitTorrent, and proposes a logarithmic-based Adaptive Trust Sampling (ATS) strategy for P2P traffic identification. In the whole process of sampling identification for P2P traffic, the sampling ratio of the current node in a P2P network can automatically adjust and dynamically vary according to the estimator of P2P traffic ratio of historical cycles. The experimental results show that the Adaptive Trust Sampling strategy can adapt to the dynamic change of sample size, effectively reduce the total sample size, mitigate the consumptions of system resources to some extent, and achieve the purpose of P2P traffic sampling.

An Adaptive Trust Sampling Method for P2P Traffic Inspection