%0 Journal Article
%T Clustering Intrusion Detection Model Based on Grey Fuzzy K mean Clustering
%A XU Yan-qun
%A ZHANG Bin
%A QIN Xiao-tie
%J Journal of Chongqing Normal University
%D 2013
%I Chongqing Normal University
%X K means clustering algorithm is applied to the field of intrusion detection£¬it has the following problems.First£¬cluster analysis does not consider the correlation degree of the data flow£¬so clustering accuracy is not high£»the second is prone to packet loss omissions because of data overload.In order to improve the clustering accuracy£¬this paper introduces grey analysis algorithm to improve the clustering accuracy.Meanwhile£¬in order to avoid the packet loss and underreporting phenomenon£¬we introduce clustering technology into the intrusion detection system to process the load balancing of the data stream£¬thereby overcome the contradiction between the high speed network data flow and low speed intrusion detection system processing capabilities.After a comprehensive analysis£¬this paper proposed an intrusion detection model based on the gray K means clustering algorithm.
%K clustering system£»intrusion detection£» K mean clustering algorithm£»cluster analysis
%U http://journal.cqnu.edu.cn/1301/pdf/130118.pdf