An Improved Hidden Markov Model for Anomaly Detection Using Frequent Common Patterns

Host-based intrusion detection techniques are needed to ensure the safety and security of software systems, especially, if these systems handle sensitive data. Most host-based intrusion detection systems involve building some sort of reference models offline, usually from execution traces (in the absence of the source code), to characterize the system healthy behavior. The models can later be used as a baseline for online detection of abnormal behavior. Perhaps the most popular techniques are the ones based on the use of Hidden Markov Models (HMM). These techniques, however, require long training time of the models, which makes them computationally infeasible, the main reason being the large size of typical traces.

Provided by: Concordia University Topic: Security Date Added: May 2012 Format: PDF

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