| 基于机器学习的入侵检测方法实验与分析 |
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| 引用本文： | 孙宏伟,邹涛,田新广,张尔扬.基于机器学习的入侵检测方法实验与分析[J].计算机工程与设计,2004,25(5):694-696. |
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| 作者姓名： | 孙宏伟 邹涛 田新广 张尔扬 |
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| 作者单位： | 1. 国防科技大学,电子科学与工程学院,湖南,长沙,410073
2. 国防科技大学,电子科学与工程学院,湖南,长沙,410073;北京首信股份有限公司IP网络技术研究所,北京,100016 |
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| 基金项目： | 普天首信重大科研基金(021125) |
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| 摘 要： | 入侵检测系统(IDS)是保障信息安全的重要手段。分析了机器学习应用于网络连接级的异常检测模型的过程，然后建立了异常检测系统原型，以验证此方法用于IDS的可能性及所能达到的性能。实验以DARPA网络数据为例，对数据的特征进行了分析、选取及构造，并针对多种情况进行了测试。实验结果表明，该IDS系统具有很好的检测性能。最后对结果进行了分析，并得出了几个有用的结论。
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| 关 键 词： | 机器学习 入侵检测方法 入侵检测系统 IDS 异常检测模型 分类模型 |
| 文章编号： | 1000-7024(2004)05-0694-03 |
Experiments and analysis for intrusion detection method based on machine learning |
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| SUN Hong-wei,ZOU Tao,TIAN Xin-guang,ZHANG Er-yang Institute of Electronic Science and Engineering,National University of Defense Technology,Changsha ,China,IP Network Technology Institute,Beijing Capitel Co Ltd,Beijing ,China.Experiments and analysis for intrusion detection method based on machine learning[J].Computer Engineering and Design,2004,25(5):694-696. |
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| Authors: | SUN Hong-wei ZOU Tao TIAN Xin-guang ZHANG Er-yang Institute of Electronic Science and Engineering National University of Defense Technology Changsha China IP Network Technology Institute Beijing Capitel Co Ltd Beijing China |
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| Affiliation: | SUN Hong-wei,ZOU Tao,TIAN Xin-guang,ZHANG Er-yang Institute of Electronic Science and Engineering,National University of Defense Technology,Changsha 410073,China,IP Network Technology Institute,Beijing Capitel Co Ltd,Beijing 100016,China |
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| Abstract: | Intrusion detection system(IDS)is a very important instrument in the domain of information security.Machine
learning was used to construct an IDS model on network connection level in order to test the feasibility and its performance.Ex-
perimental results using a set of benchmark data from DARPA have shown that the performances of this anomaly detection system
are fairly high.At the end,some useful conclusions were drawn according to the results. |
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| Keywords: | IDS machine learning anomaly detection classification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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