Method for anomaly detection based on classifier with time function
Tao Liu, Ailing Qi, Hou Yuan-bin, Chang Xin-tan · 2008
In this paper, a method combining Bayesian statistical model with function of time slicing is presented, which is used for network anomaly detection. By using Bayesian statistical model with time function, the method is intended to find and determine anomaly in the computer network. Combining the advantages of Bayesian theorem when solving uncertain problems with the function whose network traffic change with time, the purpose is 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. It has been proved by a simulation experiment that anomaly behavior will be effectively analyzed by Bayesian statistical model with time slicing.