关键词: 网络流量分类, 特征产生, 特征选择, 遗传算法

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