Research on intrusion detection of SVM based on PSO
Tiejun Zhou, Yang Li, Jia Li · 2009
Intrusion detection plays more important role in network security today. This paper introduces a method, particle swarm optimization and support vector machine, to intrusion detection system, and presents a new design of ID Based on particle swarm optimization and support vector machine. This paper presents an optimal selection approach of the SVM parameters (regulation parameter C and the radial basis function width parameter sigma ) based on particle swarm optimization algorithm. The experiments show that the optimal parameter selection approach based on PSO is available and the research of intrusion detection based on particle swarm optimization and support vector machine is effective in reducing the number of alerts, false positive, false negative better.