Anomaly Detection Using Integration Model of Vector Space and Network Representation

We propose the Eigen Co-occurrence Matrix (ECM) method, which is a modeling method for tracking the behaviors of an individual, system, or network in terms of event sequences of discrete data. Our method uses the correlation between events in a sequence to extract distinct characteristics. A key idea behind the ECM method is to regard a sequence as a serialized sequence that originally had structural relations and to extract the embedded dependencies of the events. To test its retrieval performance, we applied the ECM method to the problem of anomaly detection in intrusion detection systems. Specifically, we used the method to model a UNIX command sequence and attempted to detect intruders masquerading as valid users. The experimental results reveal that the ECM method offers distinct characteristic models for analyzing event sequences.