Intrusive Detection Systems Design based on BP Neural Network

摘要：

Objective: An intrusion detection system was constructed on the basis of the characteristics of BP neural network model. Methods: According to the capture engine of the text, all network data stream flowed through the systematic monitoring network segment will be captured, feature extraction module analyze and process the captured network data flow, you can extract complete and accurate eigenvector on behalf of this data stream, and this eigenvector will be presented to the neural network classification engine, as the input vector of a neural network. Results: The neural network classification engine analyzes and processes this eigenvector, and thus distinguishes whether it is the intrusive action.

关键词： BP neural network Intrusion detection system design

作者: Zhang Wei Wang Hao-yu Zhu Xu Zhou Yu-xin Wei Ai-guo

作者单位: Military Traffic College Tianjin, the Peoples Republic of China Command Department of Military Traffic College Tianjin, the Peoples Republic of China Military Department of Nankai University Tianjin, China Foundational Department of Military Traffic College Tianjin, the Peoples Republic of China

会议类型: 国际会议

会议名称: 第九届分布式计算及其应用国际学术研讨会

会议地点: 香港

会议语种:英文

页码: 462-465

在线出版日期: 2010-08-12（万方平台首次上网日期，不代表论文的发表时间）