An adaptive detection of anomalies in user's behavior

We propose an adaptive approach to modeling user's behavior in computer anomaly detection systems. As a base model, Markov chains with variable memory length are used. An adaptive version of the algorithm constructing a model that takes into account changes in user's behavior is introduced. Experimental testing of the proposed approach is also provided.