Abstract: In order to improve the network security intrusion detection accuracy, proposes a quantum particle swarm optimization (QPSO) optimized least square support vector machine (LSSVC) network anomaly detection method (QPSO-LSSVC) .The first use of the quantum particle swarm algorithm for the parameters of LSSVC model search, optimal parameters, and then the generalization ability of excellent LSSVC modeling and detection for network intrusion.Select the KDDCUP99 data on QPSO-LSSVC performance testing, the experimental results show that, QPSO-LSSVC improves the network anomaly detection accuracy, reduce the rate of false positives, provides effective guarantee for network security.