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2008 Third International Conference on Convergence and Hybrid Information Technology
Intrusion Detection Systems have been widely used to overcome security threats in computer networks and to identify unauthorized use, misuse, and abuse of computer systems. Anomaly-based approaches in Intrusion Detection Systems have the advantage of being able to detect unknown attacks; they look for patterns that deviate from the normal behavior. In this paper we proposed Hierarchical Gaussian Mixture Model (HGMM) a novel type of Gaussian Mixture which detects network based attacks asdoi:10.1109/iccit.2008.17 fatcat:s566ekhbybht3pwpq62337354y