Study on intrusion detection system based on heuristic support vector classification machines
Jie Liu · Qiye jishu kaifa · 2008
This article advances that put the fast learning algorithm of heuristic support vector machine applied in intrusion detection system that aiming at the problem of determining deficiency by experience which exist in the parameters of support vector machines. In order to make support vector classifier obtain better classification performance, this thesis uses heuristic rules to select the most advantageous samples, and determine the parameters of SVM by train them. In order to improve the learning speed, it uses the inner product matrix decomposing algorithm to improve the classifying speed. The results of experiment show that the intrusion detection system (IDS) based on the heuristic support vector classification machines possesses better than the IDS based on Standards SVM.