Bayesian network intrusion detection method based on credibility of mutual information
Lou Yi · Jisuanji gongcheng yu sheji · 2009
Traditional Bayesian intrusion detection algorithm does not consider the influence caused by different properties and weights of the properties,so the classification accuracy rate is not high enough.Aiming at the shortage of traditional Bayesian intrusion detection algorithm,a Bayesian network intrusion detection method based on credibility of mutual information is proposed.After considering the characteristics of network intrusion detection data and the merits of traditional Bayesian classification,credibility of mutual information is used to select feature,and some redundant properties are deleted.The credibility as weights is introduced Bayesian classifier in order to get optimized Bayesian network intrusion detection algorithm(MI-NB).Experiments show that MI-NB algorithm can greatly reduce the dimension of classification data and has higher classification accuracy rate than the traditional intrusion detection algorithm and the improved algorithm.