Application of an Improved K-means Algorithm in Intrusion Detection
Fengbin Zhang · Computer Knowledge and Technology · 2009
Traditional clustering algorithm has a lot of shortcomings ,therefore need to do further study.Through studying the traditional K-means algorithm and the K-means algorithm of entropy-weighted measure,an improved K-means algorithm of entropy-weighted measure is proposed,the algorithm uses a new method of calculating the distance of the objects not only make the distance between any objects close as much as possible in the same cluster,but also make the distance between any objects as large as possible in the different clusters. Through the KDD Cup99 data set simulation experiment,showing that the algorithm has a strong applicability and self-adaptability.