| A Novel Model of IDS Based on Fuzzy Cluster and Immune Principle |
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| 作者姓名： | TAOXin-min LIUFu-rong |
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| 作者单位： | CommunicationDepartment,HarbinInstituteofTechnology,Harbin150001,Heilongjiang,China |
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| 摘 要： | This paper presents a novel intrusion detection model based on fuzzy cluster and immune principle. The original rival penalized competitive learning (RPCI.) algorithm is modified in order to address the problem of different variability of variables and correlation between variables, the sensitivity to initial number of clusters is also solved. Especially, we use the extended RPCL algorithm to determine the initial number of clusters in the fuzzy cluster algorithm. The genetic algorithm is used to optimize the radius deviation for the determination of characteristic function of abnormal subspace.
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| 关 键 词： | 入侵检测 模糊簇 RPCL 遗传算法 免疫法则 计算机网络 网络安全 |
| 收稿时间： | 10 May 2004 |
A novel model of IDS based on fuzzy cluster and immune principle |
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| TAOXin-min LIUFu-rong.A Novel Model of IDS Based on Fuzzy Cluster and Immune Principle[J].Wuhan University Journal of Natural Sciences,2005,10(1):157-160. |
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| Authors: | Tao Xin-min Liu Fu-rong |
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| Institution: | (1) Communication Department, Harbin Institute of Technology, 15001, Heilongjiang Harbin, China |
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| Abstract: | This paper presents a novel intrusion detection model based on fuzzy cluster and immune principle. The original rival penalized competitive learning (RPCL) algorithm is modified in order to address the problem of different variability of variables and correlation between variables, the sensitivity to initial number of clusters is also solved. Especially, we use the extended RPCL algorithm to determine the initial number of clusters in the fuzzy cluster algorithm. The genetic algorithm is used to optimize the radius deviation for the determination of characteristic function of abnormal subspace. |
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| Keywords: | intrusion detection fuzzy cluster RPCL genetic algorithm correlation |
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