Study on Feature Extraction Based on Principal Component Analysis in Intrusion Detection System
Jun Guo · Microelectronics & Computer · 2006
The first problem which should to be solved in intrusion detection system based on pattern recognition method is reducing data dimentions. Because principal component analysis has two attributes we expected, one is that various principal component is not relevant, and the other is that each principal component is linear combination of all original features, the authors apply the principal component analysis to extracting features from intrusion detection system. Firstly, we use ReliefF to get rid of features that are irrelevant with classification from original features, then employ principal component analysis. The experimental results on real KDD CUP’99 dataset show that the proposed method is effective and practicable.