关键词: 网络入侵, 相关向量机, 参数选择, 粒子群优化算法, 精英选择策略

Abstract: In order to improve the detection precision of network intrusion, this paper proposes a novel network intrusion detection model based on relevance vector machine optimized by particle swarm optimization algorithm with elite election strategy. The parameters of relevance vector machine are encoded into particles, and network intrusion detection rate is taken as the search goal of particle swarms, and then particle swarm optimization algorithm is used to solve the parameters optimization problem in which elite election strategy is introduced to improve the search performance. Network intrusion detection model is established based on the optimal parameters of relevance vector machine, and the simulation experiments are carried out on the KDD99 dataset. The simulation results show that the proposed model has solved parameters optimization problem of relevance vector machine and improved intrusion detection rate compared with reference models.

Key words: network intrusion, relevance vector machine, parameters selection, particle swarm optimization algorithm, elite strategy