Method for network anomaly detection based on Bayesian statistical model with time slicing

A method combining Bayesian statistical model with time slicing function is investigated to detect network anomaly. On the basis of analyzing Bayesian theory and rules of network traffic changing with time, the advantages of Bayesian theorem in solving uncertain problems were combined with the function whose network traffic changes with time. The purpose was to establish anomaly intrusion detection model for the network activity so as to determine the occurrence of network anomaly by discovering the relationship among mass events and classifying network system behavior. Simulation experimental results show that anomaly behavior is effectively detected by the method.