The application of Fuzzy clustering number algorithm in network intrusion detection
In view of the defects of K-means algorithm in intrusion detection:the need of preassign cluster number and sensitive initial center and easy to fall into local optimum,this paper puts forward a fuzzy clustering algorithm.The fuzzy rules are utilized to express the invasion features,and standardized matrix is adopted to further process so as to reflect the approximation degree or correlation degree between the invasion indicator data and establish a similarity matrix.The simulation results of KDD CUP1999 data set show that the algorithm has better intrusion detection effect and can effectively detect the network intrusion data.
K-means algorithm Fuzzy clustering number Intrusion detection
Guo Lang
Chengdu vocational technical college,Chengdu,China 610041
国际会议
杭州
英文
3145-3147
2013-03-22（万方平台首次上网日期，不代表论文的发表时间）