Network Intrusion Feature Extraction Based on Knowledge Reduction
Yongxiang Xia · Jisuanji gongcheng · 2011
In order to improve the performance of Intrusion Detection System(IDS),this paper proposes a feature extraction method based on knowledge reduction.Rough set theory is used to do the formal description for IDS.Knowledge reduction is used to extract attribute features.Information loss and information gain are individually used to control the discrete procedure of continuous value attributes and the reduction of attribute features.Experimental result justifies that the method can eliminate the redundant information and noise of initial data effectively.