| Intelligent Intrusion Detection System Model Using Rough Neural Network |
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| 作者姓名： | YAN Huai-zhi HU Chang-zhen TAN Hui-min .Information Security and Counter-Measure Technology Research Center Beijing Institute of Technology Beijing China .National Key Laboratory of Mechatronics Engineering and Control Beijing Institute of Technology Beijing China |
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| 作者单位： | YAN Huai-zhi 1，2，HU Chang-zhen 1，2，TAN Hui-min 1，21.Information Security and Counter-Measure Technology Research Center，Beijing Institute of Technology，Beijing 100081，China; 2.National Key Laboratory of Mechatronics Engineering and Control，Beijing Institute of Technology，Beijing 100081，China |
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| 基金项目： | SupportedbytheNationalDevelopmentandReformCommissionofChina(20021823)andtheEducationMinistryofChina(200492038) |
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| 摘 要： | A model of intelligent intrusion detection based on rough neural network (RNN), which combines the neural network and rough set, is presented. It works by capturing network packets to identify network intrusions or malicious attacks using RNN with sub-nets. The sub-net is constructed by detection-oriented signatures extracted using rough set theory to detect different intrusions. It is proved that RNN detection method has the merits of adaptive, high universality, high convergence speed, easy upgrading and management.
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| 关 键 词： | 智能入侵检测系统 网络安全 神经网络 粗糙集 |
| 收稿时间： | 20 May 2004 |
Intelligent intrusion detection system model using rough neural network |
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| YAN Huai-zhi ,,HU Chang-zhen ,,TAN Hui-min ,.Information Security and Counter-Measure Technology Research Center,Beijing Institute of Technology,Beijing ,China, .National Key Laboratory of Mechatronics Engineering and Control,Beijing Institute of Technology,Beijing ,China.Intelligent Intrusion Detection System Model Using Rough Neural Network[J].Wuhan University Journal of Natural Sciences,2005,10(1):119-122. |
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| Authors: | Yan Huai-zhi Hu Chang-zhen Tan Hui-min |
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| Institution: | (1) Information Security and Counter-Measure Technology Research Center, Beijing Institute of Technology, 100081 Beijing, China;(2) National Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, 100081 Beijing, China |
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| Abstract: | A model of intelligent intrusion detection based on rough neural network (RNN), which combines the neural network and rough set, is presented. It works by capturing network packets to identify network intrusions or malicious attacks using RNN with sub-nets. The sub-net is constructed by detection-oriented signatures extracted using rough set theory to detect different intrusions. It is proved that RNN detection method has the merits of adaptive, high universality, high convergence speed, easy upgrading and management. |
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| Keywords: | network security neural network intelligent intrusion detection rough set |
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