Feature selection algorithm toward abnormal traffic detection

doi:10.3778/j.issn.1002-8331.2010.28.035

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-ying^1，2，SHAO Zhi-qing¹，CHEN Li-qiong¹

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.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

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

CLC Number:

TP319

WANG Xiu-ying^1，2，SHAO Zhi-qing¹，CHEN Li-qiong¹. Feature selection algorithm toward abnormal traffic detection[J]. Computer Engineering and Applications, 2010, 46(28): 125-127.

王秀英^1，2，邵志清¹，陈丽琼¹. 异常流量检测中的特征选择[J]. 计算机工程与应用, 2010, 46(28): 125-127.

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Feature selection algorithm toward abnormal traffic detection

异常流量检测中的特征选择

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