SVM Based P2P Traffic Identification Method With Multiple Properties

Abstract

With the rapid development of the Internet, P2P has become the main network application in the Internet, which consumes most of the network resources. Accurately identifying and making control of the P2P traffic is of great significance. As a mature classification theory, support vector machine (SVM) algorithm is suitable for P2P traffic identification. This paper proposes a SVM based P2P flow identification method, adopting multidimensional flow properties as the input vector, which can improve the P2P flow classification accuracy. Analysis shows this method has many advantages over the other methods.