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In this paper, the authors proposed a Support Vector Machine (SVM) awareness model based on Genetic Algorithm (GA) Optimization for Peer-To-Peer (P2P) network traffic. On the basis of traffic feature, they created a traffic awareness model which introduced SVM as well as utilized GA to optimize the required feature samples, avoiding the computing complexity caused by redundant sample information therefore perceiving the unknown large amount of P2P traffic effectually while representing good performance in encrypted P2P traffic awareness. As resulted from analysis and experiments, the proposed model has great real-time online performance, mean while, the expected awareness accuracy could be achieved.
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