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A Novel Model of IDS Based on Fuzzy Cluster and Immune Principle 认领 引用 被引量：1
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作者 TAOXin-min LIUFu-rong 《Wuhan University Journal of Natural Sciences》 EI CAS 2005年第1期157-160,共4页
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 diff... 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. 展开更多
关键词 intrusion detection fuzzy cluster RPCL genetic algorithm correlation
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