Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (28): 125-127.DOI: 10.3778/j.issn.1002-8331.2010.28.035

• 网络、通信、安全 • Previous Articles     Next Articles

Feature selection algorithm toward abnormal traffic detection

WANG Xiu-ying1,2,SHAO Zhi-qing1,CHEN Li-qiong1   

  1. 1.College of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China
    2.Department of Computer and Information,Shanghai Xinqiao Vocational and Technical College,Shanghai 200237,China
  • Received:2009-03-04 Revised:2009-04-20 Online:2010-10-01 Published:2010-10-01
  • Contact: WANG Xiu-ying

异常流量检测中的特征选择

王秀英1,2,邵志清1,陈丽琼1   

  1. 1.华东理工大学 信息科学与工程学院,上海 200237
    2.上海新侨职业技术学院 计算机信息系,上海 200237
  • 通讯作者: 王秀英

Abstract: Focusing on the problem of dimension reduction in abnormal network traffic detection in LAN,a novel algorithm for feature selection is proposed based on information entropy.Firstly,the features whose importance coefficient is less than a threshold are deleted,and the important features set is obtained.Secondly,the redundancy features are deleted through computation of redundancy coefficient between two features.At last,the ID3 algorithm is used to detect abnormal traffic with the reduction of feature set.And the results show that the proposed algorithm to select feature is effictive.

Key words: Feature selection, Abnormaly traffic, Information entropy, ID3 algorithm

摘要: 针对异常流量检测领域的高维数据降维问题,提出了一种基于信息熵理论的特征选择算法。首先计算特征的重要系数,删除重要系数小于一定阈值的特征,得到重要特征集。然后,计算特征间的冗余系数,删除冗余特征,得到精简的特征集。最后,用ID3算法对精简的特征集进行了验证,结果表明这种特征选择算法是有效的。

关键词: 特征选择, 异常流量, 信息熵, ID3算法

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