High Efficient Intrusion Detection Methodology with Twin Support Vector Machines
Xuejun Ding, Guiling Zhang, Yongzhen Ke, Baolin Ma, Zhichao Li · 2008
Intrusion detection has become the important component of the network security. Many intelligent intrusion detection models are proposed, but the performance and efficiency are not satisfied to real computer network system. This paper extends these works by applying a new high efficient technique, named Twin Support Vector Machines ( TWSVM), to intrusion detection. Using the KDD'99 data set collected at MIT’s Lincoln Labs evaluates the performance and efficiency of the proposed intrusion detection models. The experimental results indicate that the proposed models based on TWSVM is more efficient and has higher detection rate than conventional SVM based model and other models.