Network Intrusion Detection by a Hybrid Method of Rough Set and RBF Neural Network

摘要：

In order to detect the intrusion for computer network accurately,the network intrusion detection method should be developed continuously.The hybrid method of rough set and RBF neural network is presented to network intrusion detection.The collected 390 cases in KDD-CUP99 applied to research the performance of rough set and RBF neural network compared with RBF neural network,BP neural network.The collected 390 cases include 200 normal data,50 Probe fault data,40 U2R fault data,50 DoS fault data and 50 R2L fault data.It is indicated that the detection accuracies of rough set-RBF neural network are higher than those of normal RBF neural network and BP neural network.

关键词： RBF neural network network intrusion rough set fault data

作者: Lin Li-zhong Liu Zhi-guo Duan Xian-hui

作者单位: ShiJiaZhuang College ShiJiaZhuang 050035,China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Education Technology and Computer(第二届IEEE教育技术与计算机国际会议 ICETC 2010)

会议地点: 上海

会议语种:英文

页码: 317-320

在线出版日期: 2010-06-22（万方平台首次上网日期，不代表论文的发表时间）