One key problem for intrusion detection system is the correctness and efficiency of detection algorithm.This paper presents a revised detection algorithm through the use of Bayes decision. Bayes decision is a random pat-tern classified recognition method of the pattern recognition theory. The algorithm in this paper is designed refer tothe lest-risk Bayes decision. Experiments show that this algorithm has better performance. In the paper,we firstly in-troduce the Bayes algorithm and threshold selection algorithm. Then depending on the decision,the detection algo-rithm of intrusion detection system is designed. In the end,the experiment results are provided.
When traditional Intrusion Detection System(IDS) is used to detect and analyze the great flow data transfer in high-speed network,it usually causes the computation bottleneck. This paper presents a new Mobile Agent Distributed IDS(MADIDS) system based on the mobile agents. This system is specifically designed to process the great flow data transfer in high-speed network. In MADIDS,the agents that are set at each node process the data transfer by distributed computation architecture. Meanwhile by using the reconfiguration quality of the mobile agents ,the load balance of distributed computation can be dynamically implemented to gain the high-performance computing ability. This ability makes the detecting and analyzing of high-speed network possible. MADIDS can effectively solve the detection and analysis performance bottleneck caused by the great flow data transfer in high-speed network. It enhances the performance of IDS in high-speed network. In this paper,we construct the infrastructure and theoretical model of MADIDS,and the deficiencies of MADIDS and future research work are also indicated.
