FCM Algorithm Based on Box-FCM Statistics and its Application in Network Intrusion Detection
Sun Wen · 2008
This paper carried experiments on the traditional FCM (Fuzzy C Means) algorithm by using KDDCup99 intrusion-detection data of network and found that when clustering division and isolated-point judgments were carried out, phenomenon of rough division was existed in this algorithm. To this question the paper presented that classifying and describing the distribution of data sets by using of the statistics box-FCM methods. Compared with the original algorithm it didn’t need to update the clustering center frequently and could resolve time-consuming problems effectively. Finally this paper combined feature matching with box-FCM algorithm so that network connection data records could be coordinated analyzed. Experiments proved that the detection efficiency of this real-time method was improved noticeably and some new intrusion ways could be detected to update the knowledge base.