现代电子技术2016，Vol.39Issue(20)：12-14,19,4.DOI:10.16652/j.issn.1004-373x.2016.20.004
群智能算法优化神经网络在网络安全的应用
Application of swarm intelligence algorithm optimizing neural network in network security
摘要
Abstract
The application of swarm intelligence optimizing neural network in network security and a network traffic detec⁃tion model based on neural network algorithm are studied in this paper. QAPSO algorithm is used to optimize the basis function center and base function width of RBF neural network,and the connection weights of the output layer and the hidden layer as well. The detection model studied in this paper is analyzed by means of an example. The collected data is used to train the net⁃work traffic identification system and test its performance. The method researched in this paper is compared with the algorithms based on the conventional PSO and HPSO. The results show that the detection method has a faster recognition speed and better recognition accuracy,and can avoid the occurrence of local optimal solutions.关键词
网络流量检测/群智能算法/RBF神经网络/网络安全Key words
network traffic detection/swarm intelligence algorithm/RBF neural network/network security分类
信息技术与安全科学引用本文复制引用
何欢..群智能算法优化神经网络在网络安全的应用[J].现代电子技术,2016,39(20):12-14,19,4.基金项目
国家自然科学基金 （）
