A Bayesian trust sampling method for P2P traffic inspection

A Peer-to-Peer (P2P) traffic identification method based on Bayesian trust sampling is presented in this paper, which predicts the fluctuation degree for next cycle of P2P traffic ratio, and optimizes for the used amount of historical proportion estimation. 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.