Application of Improved Support Vector Machines in Network Intrusion Detection

In order to improve the security of the network, this paper proposes an improved support vector machine algorithm for network intrusion detection.Firstly, kernel principal component analysis is used to extract data network feature, accelerate the network intrusion detection rate, then the particle swarm optimization algorithm is used to optimize the support vector machine parameters, improve the network detection accuracy rate.The simulation results show that, the proposed method has improved network intrusion detection rate, reduce the failure rate, and speed the network intrusion detection, it is an efficient, real-time network intrusion detection algorithm.