关键词: 网络入侵检测, 特征选择, 粒子群优化算法, K最近邻

Abstract: In order to improve network intrusion detection performance, this paper proposes a network intrusion detection model based on particle swarm optimization and k-nearest neighbor. Firstly, the features and KNN’s parameters are taken as a particle, and then the optimal features and KNN’s parameters are got by particle swarm to build the optimal network intrusion detection model, finally, the performance of the built model is tested by KDD 1999 data. Experimental results show that the proposed algorithm is more effective for feature selection of network data and improvement of network intrusion detection speed and detection rate of classification algorithms.

Key words: network intrusion detection, features selection, particle swarm optimization algorithm, k-nearest neighbor