| 径向基神经网络在入侵检测中的应用 |
| |
| 引用本文： | 滕少华,王琳.径向基神经网络在入侵检测中的应用[J].江西师范大学学报(自然科学版),2007,31(3):297-301. |
| |
| 作者姓名： | 滕少华 王琳 |
| |
| 作者单位： | 1. 广东工业大学,计算机学院,广东,广州,510006
2. 中国电子科技集团公司第七研究所,广东,广州,510006 |
| |
| 基金项目： | 广东省自然科学基金(06021484,04107411)，广东省科技计划(2005B16001095,2005B10101077)资助项目 |
| |
| 摘 要： | 与广泛使用的BP网络模型相比,径向基函数神经网络具有训练时间短且不易收敛到局部最小的优点.将3种径向基神经网络应用到入侵检测中,用于入侵模式识别的分类和预测,从而提高入侵检测系统的检测率并降低误报率.
|
| 关 键 词： | 入侵检测 径向基神经网络 BP神经网络 |
| 文章编号： | 1000-5862（2007）03-0297-04 |
| 修稿时间： | 2006-12-26 |
Application of Radial Basis Function Neural Network in Intrusion Detection |
| |
| TENG Shao-hua,WANG Lin.Application of Radial Basis Function Neural Network in Intrusion Detection[J].Journal of Jiangxi Normal University (Natural Sciences Edition),2007,31(3):297-301. |
| |
| Authors: | TENG Shao-hua WANG Lin |
| |
| Institution: | 1. College of Computer, Guangdong University of Technology, Guangzhou 510006, China; 2. China Electronics Technology Group Corporation No. 7 Research Institute, Guangzhou 510006, China |
| |
| Abstract: | In this paper,three radial basis function neural network models are presented for intrusion detection classification and prediction.Compared with the widely used back propagation neural network,they take shorter time in training and hardly converge to local minimization.Thus,they increase detection rate and reduce false positive rate of an intrusion detection system. |
| |
| Keywords: | intrusion detection RBF neural network BP neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
