Efficient K-means Algorithm in Intrusion Detection
Wenjun Yang · 2017
In order to improve the detection rate of invasion, reduce false detection rate and put forward a method based on density and maximum distance of k means clustering algorithm, the clustering results used in intrusion detection, improved the original algorithm in the choice of initial clustering center, simplify the computational complexity of the algorithm.Finally simulation experiments using KDD Cup 99 data set.Results show that the model can obtain ideal intrusion detection rate and false detection rate.