Markov chains, classifiers, and intrusion detection

Abstract: This paper presents a statistical anomaly detection algorithm based on Markov chains. Our algorithm can be directly applied for intrusion detection by discovering anomalous activities. Our framework for constructing anomaly detectors is very general and can be used by other researchers for constructing Markov-chain-based anomaly detectors. We also present performance metrics for evaluating the effectiveness of anomaly detectors. Extensive experimental results clearly demonstrate the effectiveness of our algorithm. We discuss several future directions for research based on the framework presented in this paper.