APPLYING BAYESIAN TRUST SAMPLING TO P2P TRAFFIC INSPECTION

摘要

This paper presents a peer-to-peer (P2P) traffic identification method based on Bayesian trust sampling and predicts the fluctuation degree for next cycle of P2P traffic ratio by Bayesian trust method, which provides the basis for the setting of sampling parameters. This paper also does the optimization for the used amount of historical proportion estimation in Bayesian trust model. Simulation results show that, under the premise of using a fixed number of the estimated values for historical P2P ratio, this trust method makes a better forecast for the fluctuation degree of P2P traffic ratio and reduces the amount of redundant samples. The sampling results also show that errors of estimated value are roughly in line with the preset precision range.