Network Intrusion Detection Method Based on High Speed and Precise Genetic Algorithm Neural Network
作者： Jingwen Tian , Meijuan Gao
关键词:
摘要: Aimed at the network intrusion behaviors are characterized with uncertainty, complexity, diversity and dynamic tendency advantages of neural network, an detection method based on high speed precise genetic algorithm is presented in this paper. The combined adaptive floating-point code BP which has higher accuracy faster convergence speed. We construct structure, give flow. discussed analyzed impact factor behaviors. With ability strong self-learning can detect various rapidly effectively by learning typical characteristic information. experimental result shows that feasible effective.
computer.org
sci-hub.se 参考文章(5)
Juan M. Estevez-Tapiador, Pedro Garcia-Teodoro, Jesus E. Diaz-Verdejo, Anomaly detection methods in wired networks: a survey and taxonomy Computer Communications. ,vol. 27, pp. 1569- 1584 ,(2004) , 10.1016/J.COMCOM.2004.07.002
Theuns Verwoerd, Ray Hunt, Intrusion detection techniques and approaches Computer Communications. ,vol. 25, pp. 1356- 1365 ,(2002) , 10.1016/S0140-3664(02)00037-3
John Grefenstette, Optimization of Control Parameters for Genetic Algorithms systems man and cybernetics. ,vol. 16, pp. 122- 128 ,(1986) , 10.1109/TSMC.1986.289288
Daejoon Joo, Taeho Hong, Ingoo Han, The neural network models for IDS based on the asymmetric costs of false negative errors and false positive errors Expert Systems With Applications. ,vol. 25, pp. 69- 75 ,(2003) , 10.1016/S0957-4174(03)00007-1
LU Hui-bin, Research of intrusion detection based on neural network optimized by adaptive genetic algorithm Computer Engineering and Design. ,(2008)