Application of Network Intrusion Detection Based on Two-steps Fuzzy Clustering

Fuzzy C-means clustering algorithm (FCM) is widely applied to the intrusion detection.To achieve effective division for intrusion data,a rough fuzzy clustering algorithm based on the shadow set is applied in this study.Besides,a new measure named ‘two-steps′is proposed to improve detection performance in this paper.The first step is to divide the network data into normal and intrusion types.The second step is to divide the intrusion data into specific types.This measure can improve detection performance effectively.In the simulation experiment,the KDDCUP1999 data set is used.The results of the experiment proved that the ‘two-steps′ algorithm had a relatively high detection rate in intrusion detection.