Software Defined Network separates the control plane from network equipment and has great advantage in network management\nas compared with traditional approaches. With this paradigm, the security issues persist to exist and could become even worse\nbecause of the flexibility on handling the packets. In this paper we propose an effective framework by integrating SDN and machine\nlearning to detect and categorize P2P network traffics. This work provides experimental evidence showing that our approach can\nautomatically analyze network traffic and flexibly change flow entries in OpenFlow switches through the SDN controller. This can\neffectively help the network administrators manage related security problems.
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