A feature selection algorithm design and its implementation in intrusion detection system / 西安交通大学学报·英文版

ABSTRACT

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.