Computer Science ›› 2015, Vol. 42 ›› Issue (10): 117-121.

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Peer-to-Peer Traffic identification Method Based on Chaos Particle Swarm Algorithm and Wavelet SVM

WANG Chun-zhi, ZHANG Hui-li and YE Zhi-wei   

  • Online:2018-11-14 Published:2018-11-14

Abstract: A novel peer-to-peer(P2P)traffic identification algorithm was proposed as the P2P traffic has the features of multi-scale and mutability.The identification algorithm is based on support vector machine (SVM) with the wavelet kernel function.Further,the disadvantages of long training time and easily falling into local minimum in the SVM parameters training methods were analyzed,and chaos particle swarm algorithm was employed to optimize the SVM parameters in order to improve the efficiency of parameters training and the identification accuracy.Finally,the real campus network traffic data were used to test the efficiency of the proposed method.The experimental results show that the proposed method has higher identification accuracy and computational efficiency compared with the support vector machine with the traditional kernel function and parameters training method.

Key words: P2P traffic identification,Support vector machine,Wavelet,Chaos particle swarm optimization algorithm

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