Application of network intrusion detection based on fuzzy C-means clustering algorithm

Authors:
Wuling Ren;Jinzhu Cao;Xianjie Wu
Affiliations:
College of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, Zhejiang, China;College of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, Zhejiang, China;Modern Educational Technology Center, Zhejiang Gongshang University, Hangzhou, Zhejiang, China
Venue:
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Year:
2009

Citing 3
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Abstract

Aiming at the problem of higher false positive and missing report rate in network intrusion detection, an intrusion detection method based on clustering algorithm is proposed in this paper. This method applies Fuzzy C-means clustering Algorithm to the detection of network intrusion. Through the building of intrusion detection model, carries out fuzzy partition and the clustering of data, and this will detach normal data and attack data effectively. The experiment shows the feasibiUty and validity of Fuzzy C-means clustering algorithm.