Research And Implementation Of P2P Traffic Identification

Recent years, P2P (peer-to-peer), as a bran-new technology, has developed whip and spur. Interrelated investigation indicates that P2P traffic has taken up 60% to 80% of the total Internet traffic stealthily, it became the killer application of Broad Band Internet. P2P operation has increased constantly, it consumes network bandwidth hugely, arouses congestion of network and reduce the performance of other operations. On the other hand, for the enterprise user, inner employees use enterprise network to listen music or watch Streaming Media on the internet, this makes tremendous waste of network resource. Further more, using not safely network environment to get application program and P2P protocol may open up a back door of enterprise safety, make viruses and baleful codes able to stand aside safety check up and enter into the corporation. So, the implementation of identify P2P traffic has become a problem need to be resolved immediately.Forepart, people use port scan to. identify P2P flow which with pre-defined port number. Recently, S. Seir^[1] and W. Moore^[2] applied the application signature matching method to P2P traffic identification. The application signature matching method cramps out application signature from packets' payload and matches it with the known P2P application signature in the database. T. Karagiannis^[3] and A. W. More^[4] analyzed P2P traffic behavior and got some disciplinarians. They used these rules to identify P2P traffic. Since new generation P2P application can use arbitrary port number to avoid fixed-port block and use payload encryption to avoid P2P application signature detection, the identification of P2P traffic becomes more and more difficult. We need to find a robust and accurate P2P traffic identification scheme.So in this paper, we begin with the operating principle of P2P traffic identification. Then, we analyze the problem in the identification of P2P traffic and the needed technology to realize the effective P2P traffic identification scheme. The works this paper has done list as follows:a) Researched several kind of present solutions in P2P flow identification, analyze their features and problems in the identification process.b) We modified application signature matching method and proposed a Back-propagation Neural Network traffic recognizer using new trafficbehaviors.Put forward a P2P traffic identification resolution based on modified application signature matching and traffic recognizer using Back-propagation Neural Network, which overcome the disadvantages of present solutions in P2P traffic identification. So it has efficiently improved the recognition rate and pace of P2P flow identification.c) In order to test the new P2P traffic identification solution, this paper designed and implemented a Back-propagation Neural Network for traffic recognizer in the popular modeling software MATLAB, and then designed and implemented the P2P flow identification solution on it.d) Proved the validity of the new solution based on Deep Packet Inspection and traffic recognizer using Back-propagation Neural Network, analyzed its scalability on our test environment based on MATLAB.