Application of Modified k-means Clustering Algorithm in Intrusion Detection
Yin Yao-ren · Science Technology and Engineering · 2008
The classic algorithm of k-means is discussed,the shortages of this algorithm such as it can not deal with symbolic data and it is sensitive for data of isolation point and noise are demonstrated.A modified k-means clustering algorithm is put forward,it changes the shortcomings of k-means.Its complexity is analyzed from theoretical.The experiments show that,compared with traditional method based on means,the modified data clustering algorithm can improve the efficiency of data clustering and the accuracy of intrusion detection.