A FEATURE SELECTION ALGORITHM DESIGN AND ITS IMPLEMENTA-TION IN INTRUSION DETECTION SYSTEM
杨向荣, 沈钧毅 · 西安交通大学学报：英文版 · 2003
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.