Application of improved information gain algorithm in intrusion forensics
Wei Gong · Journal of Computer Applications · 2011
Feature selection algorithm based on the Information Gain(IG) can solve the problem of high-dimension and magnanimous data in intrusion forensics,but it neglects the correlation between features,which can lead to the redundancy of features,and affect the speed and accuracy of intrusion forensics.Therefore,an Improved Information Gain(IIG) algorithm based on feature redundancy was proposed.In the improved algorithm,the irrelevant features and the redundant features were removed by adding the judgments of redundancy between features,which effectively simplified feature subset.The experimental results show that the proposed algorithm can effectively select features,ensure detection accuracy and improve processing speed.