| 基于支持向量机的网络入侵异常检测 |
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| 引用本文： | 张晨,王晓东. 基于支持向量机的网络入侵异常检测[J]. 重庆理工大学学报(自然科学版), 2007, 0(12) |
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| 作者姓名： | 张晨 王晓东 |
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| 作者单位： | 昆明理工大学信息工程与自动化学院 昆明650051 |
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| 摘 要： | 针对入侵检测系统(IDS)这门新兴的安全技术,提出了一种基于支持向量机的网络入侵异常检测模型,以支持向量机(SVM)的二类分类能力对网络入侵进行异常检测,实验结果与ANN方法结果相比较证明:该方法具有较高的准确性,而且可以大大缩短训练与检测时间.
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| 关 键 词： | 网络安全 支持向量机 网络入侵 异常检测 |
Network Intrusion Abnormal Detection Based on Support Vector Machine |
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| ZHANG Chen,WANG Xiao-dong. Network Intrusion Abnormal Detection Based on Support Vector Machine[J]. Journal of Chongqing University of Technology(Natural Science), 2007, 0(12) |
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| Authors: | ZHANG Chen WANG Xiao-dong |
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| Abstract: | Intrusion detection system(IDS) is one kind of new developing network security technology.This paper proposes one kind of network intrusion and abnormal detection models on the basis of a network supporting vector machine,which can inspect network intrusion and abnormal detection with the class II categorized ability of support vector machine(SVM).Compared with an experimental result of ANN method,this method has higher accuracy,and shortens training and detection time greatly. |
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| Keywords: | network security support vector machine network intrusion abnormal detection |
| 本文献已被 CNKI 等数据库收录！ |
