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A FEATURE SELECTION ALGORITHM DESIGN AND ITS IMPLEMENTATION IN INTRUSION DETECTION SYSTEM

A FEATURE SELECTION ALGORITHM DESIGN AND ITS IMPLEMENTATION IN INTRUSION DETECTION SYSTEM
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摘要 Objective Present a new features selection algorithm. Methods based on rule induction and field knowledge. Results This algorithm can be applied in catching dataflow when detecting network intrusions, only the sub dataset including discriminating features is catched. Then the time spend in following behavior patterns mining is reduced and the patterns mined are more precise. Conclusion The experiment results show that the feature subset catched by this algorithm is more informative and the dataset’s quantity is reduced significantly. Objective Present a new features selection algorithm. Methods based on rule induction and field knowledge. Results This algorithm can be applied in catching dataflow when detecting network intrusions, only the sub dataset including discriminating features is catched. Then the time spend in following behavior patterns mining is reduced and the patterns mined are more precise. Conclusion The experiment results show that the feature subset catched by this algorithm is more informative and the dataset’s quantity is reduced significantly.
出处 《Journal of Pharmaceutical Analysis》 SCIE CAS 2003年第2期134-138,共5页 药物分析学报(英文版)
基金 ThisworkwassupportedbytheNationalNaturalScienceFoundationofChina(No.60173058)
关键词 network intrusion detection features selection rule induction behavior patterns mining network intrusion detection features selection rule induction behavior patterns mining
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