基于多分类器的入侵检测系统

Intrusion Detection System which Based on Multiple Classifiers

本文使用ICA与KPCA技术分别构造ICA-SVM与KPCA-SVM两个子分类器,在此基础上,构建基于多分类器的集成入侵检测系统。实验表明,该系统对入侵行为的分类正确率分别高于SVM、PCA-SVM、KPCA-SVM方法。

This paper uses the ICA and KPCA technology to construct ICA-SVM and KPCA-SVM sub-classifier, and on this basis to build intrusion detection system which based on multiple classifiers. The experiments show that the system＇s correct rate of classification to intrusion behavior is higher than the methods of SVM, PCA-SVM and KPCA-SVM.