A Cooperative Network Intrusion detection Based on Fuzzy SVMs
Hongle Du, Shaohua Teng, Naiqi Wu, Wei Zhang, Jiangyu Su · Journal of Networks · 2010
T he re is a large number of noise in the data obtained from network , which deteriorates intrusion detection performance. To delete the noise data, data preprocess ing is done before the constructi on of hyperplane in support vector machine ( SVM ) . By introduc ing fuzzy theory into SVM, a new method is proposed for network i ntrusion detection. Because the attack behavior is different for different network protocol , a different fuzzy membership function is formatted, such that for each class of protocol there is a SVM. To implement this approach, a f uzzy SVM -based cooperative network intrusion detection system with multi-agent architecture is presented. It is composed of three types of agents corresponding to TCP, UDP , and ICMP protocol s, respectively. Simulation experiment s are done by using KDD CUP 1999 data set , results show that the training time is significantly shortened, storage space requirement is reduced, and classification accuracy is improved.