JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2010, Vol. 40 ›› Issue (5): 1-7.

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Method of feature generation and selection for network traffic classification

YANG Ai-min1, ZHOU Yong-mei1, DENG He2, ZHOU Jian-feng3   

  1. 1. School of Informatics, Guangdong University of Foreign Studies, Guangzhou 510420,China;
     2. Changsha Social Work College, Changsha 410004, China;
    3. School of Management, Guangdong University of Foreign Studies, Guangzhou 510420, China
  • Received:2010-04-02 Online:2010-10-16 Published:2010-04-02

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Abstract:

In the System of Network Traffic Classification based on machine learning method, feature generation and feature selection directly affects the speed and accuracy of classification. To solve this problem, in feature generation aspect, we analyze the packet’s attributes (size, count, time, flag) and flow’s attributes (time) from the information of Packet-Level and FlowLevel, and 37 statistical features are generated. In feature selection aspect, we proposes a method of feature selection integrating Filter model and Wrapper model, to decrease the dimension of features. Experiments show the proposed methods improve the accuracy of classification.

Key words: network traffic classification, feature generation, feature selection, feature distance, genetic algorithm

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