A Discriminant Model of Network Anomaly Behavior Based on Fuzzy Temporal Inference
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International Journal of Advanced Computer Science and Applications(IJACSA) (2012)

The aim of this paper is to provide an active inference algorithm for anomalous behavior. As a main concept we introduce fuzzy temporal consistency covering set, and put forward a fuzzy temporal selection model based on temporal inference and covering technology. Fuzzy set is used to describe network anomaly behavior omen and character, as well as the relations between behavior omen and character. We set up a basic monitoring framework of anomalous behaviors by using causality inference of network behaviors, and then provide a recognition method of network anomaly behavior character based on hypothesis graph search. As shown in the example, the monitoring algorithm has certain reliability and operability.
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