基于组合分类器的校园网入侵检测

Intrusion Detection of Campus Network Based on Combined Classifier

为了增强校园网络的安全性,提出KPCA和BP神经网络相结合的组合分类器法构造入侵检测系统.先用KPCA对原始数据进行降维处理,而后用BP神经网络对新的数据进行分类检测.结果表明,该方法能有效地缩短检测时间,提高检测效率.

To improve safety of campus network,an intrusion detection system is proposed by combined classifier which is combination of KPCA technology and BP Neural Network.First,KPCA technology is used to decrease the dimensions of raw data,and then the new data samples are classified by BP neural network.Results show that the method can shorten detection time and enhance detection rate.