空军工程大学学报（自然科学版）2016，Vol.17Issue(6)：93-98,6.DOI:10.3969/j.issn.1009-3516.2016.06.017
PCA-BP神经网络入侵检测方法
A PCA BP Neural Network based Intrusion Detection Method
摘要
Abstract
Aimed at the problems that slow convergence speed,poor learning performance and other imper-fections exist in the classical BP neural network intrusion detection,a PCA�BP neural network intrusion detection method is put forward by adopting principal components analysis and additional momentum method,This method improves the classical BP neural network algorithm by data features selection and network weights amendment.Firstly,the paper standardizes the network data set,and then adopts it to deal with dimension reduction to confirm the characteristics.Finally,the paper detects the processed data set by improved BP neural network.Through the lots of experiments in KDD Cup 1 9 9 9 network data sets, the result shows that the method has better performances in system model convergence,detection efficien-cy and detection accuracy in most network environment.Especially,in training samples,the convergence of system model,the detection efficiency and the detection accuracy are better than that by using BP neural network algorithm and half�supervision intrusion detection algorithm.关键词
入侵检测系统/主成分分析/BP神经网络/附加动量法/入侵检测算法Key words
intrusion detection system/principle component analysis/back propagation neural network/additional momentum/intrusion detection algorithm分类
计算机与自动化引用本文复制引用
梁辰,李成海,周来恩..PCA-BP神经网络入侵检测方法[J].空军工程大学学报（自然科学版）,2016,17(6):93-98,6.基金项目
国家自然科学基金(61309022) （61309022）
