DocumentCode
2115517
Title
Intrusion Detection Based on Improved Fuzzy C-means Algorithm
Author
Jiang, Wei ; Yao, Min ; Yan, Jun
Author_Institution
Coll. of Comput., Zhejiang Univ., Hangzhou
Volume
2
fYear
2008
fDate
20-22 Dec. 2008
Firstpage
326
Lastpage
329
Abstract
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.
Keywords
fuzzy set theory; pattern clustering; security of data; fuzzy c-means algorithm; intrusion detection; pattern clustering; fuzzy C-means algorithm; intrusion detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Engineering, 2008. ISISE '08. International Symposium on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-2727-4
Type
conf
DOI
10.1109/ISISE.2008.17
Filename
4732404
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