An Improved Intrusion Detection System Based on Neural Network

摘要：

Neural network approach is an advanced methodology used for intrusion detection. Adaptive Resonance Theory (ART) is one kind of neural networks featuring self-organization of stable recognition categories and on-line learning. ART 2-A is a fast clustering algorithm of the ART family. But ART 2-A cannot process categorical values, while network traffic data collected for intrusion detection always contain this kind of data. An improved model of ART 2-A is thus proposed to deal with categorical data properly. To verify the accuracy of this new model, experiments were carried out on the KDD Cup 99 data set. Results showed that the performance of the new model was satisfactory.

关键词： information security intrusion detection neural network

作者: Xiao Han

作者单位: School of Software and Microelectronics,Peking University Beijing 102628,P.R.China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 887-890

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）