| 小波核支持向量机的网络入侵检测 |
| |
| 引用本文： | 旷海兰,刘新华,魏书堤,罗可. 小波核支持向量机的网络入侵检测[J]. 计算机工程与应用, 2006, 42(17): 143-145 |
| |
| 作者姓名： | 旷海兰 刘新华 魏书堤 罗可 |
| |
| 作者单位： | 衡阳师范学院计算机系,湖南,衡阳,421008;武汉理工大学信息工程学院,武汉,430070;长沙理工大学计算机与通信工程学院,长沙,410076 |
| |
| 基金项目： | 国家自然科学基金;湖南省教育厅青年基金 |
| |
| 摘 要： | 将小波理论和统计学习运用到网络入侵检测中,使用小波核支持向量机(WSVM)对网络连接信息进行攻击检测和异常发现。仿真试验结果表明,与RBF核相比,小波核支持向量机在泛化能力和检测能力方面都有所提高。
|
| 关 键 词： | 小波核函数 支持向量机 入侵检测 |
| 文章编号： | 1002-8331-（2006）17-0143-03 |
| 收稿时间： | 2006-03-01 |
| 修稿时间： | 2006-03-01 |
Network Intrusion Detection Based on Wavelet Kernel Support Vector Machine |
| |
| Kuang Hailan,Liu Xinhua,Wei Shudi,Luo Ke. Network Intrusion Detection Based on Wavelet Kernel Support Vector Machine[J]. Computer Engineering and Applications, 2006, 42(17): 143-145 |
| |
| Authors: | Kuang Hailan Liu Xinhua Wei Shudi Luo Ke |
| |
| Affiliation: | 1Computer Department, Hengyang Normal University, Hengyang, Hunan 421008; 2College of Information Engineering,Wuhan University of Technology,Wuhan 430070; 3College of Computer and Communication Engineering,Changhsa University of Technology, Changsha 410076 |
| |
| Abstract: | Wavelet theory and statistical learning are combined to apply in network intrusion detection field.Through the analysis of current intrusion detection methods and characteristic of wavelet support vector machine(WSVM),this paper tries to apply WSVM as classifying means to deal with network connecting data.The results indicate that the classifying performance of wavelet kernel support vector machine shows better than RBF kernel SVM at extending ability and precision. |
| |
| Keywords: | wavelet kernel function wavelet supporting vector machine intrusion detection |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
