Research of P2P Traffic Identification Based on BP Neural Network

Today´s P2P application is a big challenge to network traffic workload. In contrast to first generation P2P networks which used well-defined port numbers, current P2P applications have ability to disguise their existence through the use of arbitrary ports. Our goal is to give out a new approach for P2P traffic identification based BP Neural Network, and without relying on keyword matching. This article introduces BP algorithm, analyzes the characters of P2P traffic, gives out the BP network based on connection patterns ofP2P networks. The trained BPNN was applied as a P2P traffic identifier, which can be used to distinguish any kind of P2P applications from non-P2P applications. This feasible solution has many advantages in P2P traffic identification. We believe our approach is the first method for characterizing P2P traffic using network dynamics based on BP network rather than any userpayload.