Step feature selection algorithm for intrusion detection
Yunxiang Liu · Computer Engineering and Applications Journal · 2010
The intrusion detection data set is high dimensional,which leads to low processing speed for intrusion detection algorithms,but it holds many features affecting little for detection.To address the above issue,a step feature selection algorithm is proposed in this paper.Depending on the definition of relevant feature and redundant feature and using mutual information as criterion,it firstly removes the irrelevant features and then removes the redundant features.With low time complexity,the feature selection algorithm independent of detection algorithm can easily balance the detection accuracy and the number of features through threshold.Experiments over networks connection records from KDD-99 data set are implemented for many detection algorithms to evaluate the proposed method.The results show the algorithm can effectively select features,ensure detection accuracy and improve processing speed.