BP neural network has two disadvantages, one is to fall into local minimum value easily; the other is the slow convergence. We propose in this paper an approach, including three main operations. Firstly, the algorithm of particle swarm optimization (PSO) is applied to improve back propagation (BP) neural network. Secondly, principal components analysis (PCA) method is used to deal with the original information. Thirdly, after optimization of BP neural network, we employ it into the intrusion detection system. The simulation results reveal that the new proposed BP neural network is superior to the traditional BP neural network.