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P2P traffic has become one of the most significant portions of the network traffic. How to improve the accuracy of the traffic identification efficiently is still a difficult problem. A promising approach that has recently received some attention is traffic classification using machine learning techniques. In this paper, we propose a BP neural network algorithm for P2P traffic classification problem. We implement a P2P traffic identification prototype system which can realize offline learning and online classification of P2P traffic effectively. The results show that the method provides a promising way to measure aggregate P2P traffic.