Over the last few years, peer-to-peer (P2P) applications have relentlessly grown to represent a formidable component of Internet traffic. In contract to P2P networks witch used well-defined port number, current P2P applications have use of arbitrary ports. As P2P applications continue to evolve, robust and effective methods are methods are needed for P2P traffic identification. Many P2P applications are bandwidth-intensive. Understanding the Internet traffic profile is important for several reasons, including traffic engineering, network service pricing. In this Thesis, we integrated port-based method into original Classifier which is using content-based method only. Therefore, we can improve the recognition rate for Classifier and identify more applications. We also verified our Classifier recognition rate by using the results of Service Control Engine.