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
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;
Conference_Titel :
Information Science and Engineering, 2008. ISISE '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-2727-4
DOI :
10.1109/ISISE.2008.17
