【摘要】 为了提高网络入侵检测系统(IDS)的实时性、可用性以及整体性能,提出了一种自动识别特征相关性的方法(特征分类法)。用该方法提取出的互相独立(或相关性很小)的特征作为反向传播神经元网络的输入,以此为基础建立了一个IDS。实验证明该方法以及所建立的IDS效果较好。结论表明通过分类可以求得一组特征互相之间的相关程度,进一步可求得互相独立(或相关性很小)的特征。更多还原

【Abstract】 To improve the reality,useful and whole performance of network Intrusion Detection System(IDS),the solution to get independent characters used to(or evidence) IDS is presented in the paper.The approach of auto-recognition of inter-relativity of the characters is developed,which is classification method for characters.The characters picked up by the method are used as the input of back propagate neural network.The characters are inter-independent,or weak relative.On the base of the chosen charac-ters,an IDS is built.Tests show that the approach and IDS developed in the article is useful and available.It is conclusion that a set of inter-independent characters should be provided for IDS.The inter-relative degree of characters can be required by the method developed in the article.更多还原