Intrusion Detection Methods Based on PCA and Fuzzy Integration
Yong Wang · Computer Engineering and Science · 2010
In order to solve the detection performance,training time and detection time,an intrusion detection method using fuzzy integration based on two different Principal Component Analyses(PCA)feature analyses is presented. Firstly,two different PCAs is applied to network intrusion feature extraction. Then,an initial intrusion detection result is done by two KNN classifiers. The two classifiers can overcome the shortcomings of each other.The last step is to form the final result by fusing these results using fuzzy integration. Experiments have been done on the datasets in KDD-99,and the results show that the method is effective and the intrusion detection's total performance is improved.