A Hybrid Anomaly Intrusion Detection Model Based on GAFCM-SVM
The anomaly detection as a kind of intrusion detection way is good at detecting the unknown attacks or new attacks,and it has attracted much attention during recent years.A new hybrid intrusion detection model that combines the FCM based on genetic algorithm and SVM is proposed.During the process of detecting intrusion,the membership function and the fuzzy interval are applied to it,and the process is extended to soft classification from the previous hard classification.Then a fuzzy correction sub interval is introduced,so when the detection result of a data instance belongs to this range,the data will be re-detected in order to improve the efficiency of intrusion detection.Experimental results show that the anomaly intrusion detection model can effectively detect the vast majority of network attack types,which provides a feasible solution for solving the problems of false alarm rate and detection rate in anomaly intrusion detection model.
fuzzy c-means cluster support vector machine membership function anomaly intrusion detection
国内会议
湖北恩施
英文
1-8
2014-09-13（万方平台首次上网日期，不代表论文的发表时间）