Intrusion Detection Based on Improved Fuzzy C-means Algorithm

被引：10
|
作者：
Jiang, Wei [1 ,2 ]
Yao, Min [1 ,2 ]
Yan, Jun [1 ,2 ]
机构：
[1] Zhejiang Univ, Coll Comp, Hangzhou 310027, Zhejiang, Peoples R China
[2] Wuhan Univ, State Key Lab Software Engn, Wuhan 430072, Peoples R China
来源：
ISISE 2008: INTERNATIONAL SYMPOSIUM ON INFORMATION SCIENCE AND ENGINEERING, VOL 2 | 2008年
关键词：
fuzzy C-means algorithm; intrusion detection;
D O I：
10.1109/ISISE.2008.17
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Clustering is one of the important means of Intrusion detection. In order to overcome the disadvantages of fuzzy C-means algorithm, this paper presents a kind of improved fuzzy C-means algorithm (IFCM for short). IFCM algorithm reduces the infection of isolated point by means of weighting the degree of membership for objects to be clustered, and avoids the subjectivity in choosing the number of clustering by introducing the function of validity. Then, IFCM algorithm is used to intrusion detection, and satisfactory experiment effects are obtained.
引用
收藏
页码：326 / +
页数：2
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