A New Intrusion Detection Technology by Markov Chain

In order to reduce wrong detection intrusions, missed intrusions and poor real-time performance. An intrusion detection method based on Markov chain was presented. For every network packet, three major groups of features were extracted, and feature sequence was matched into the state of Markov process. Then anomaly activity of network could be detected by constructing Markov chain. Moreover, using a dynamic load-balancing algorithm, it could avoid packet loss in high-performance network and process heavy traffic loads in real-time. Experiment analysis proves that this intrusion detection method has relatively low false positive rate and false negative rate.