Heuristic Anomaly Detection Model of Industrial Control System Based on Combined Neural Network

Abstract:

In order to improve the intrusion detection rate of industrial control system, the principle of traditional industrial intrusion detection technology is discussed, and the comparative study is done from the viewpoint of information theory. The dynamic and static fingerprints of industrial control attacks in the protocol stack, statistical characteristics, and communication behavior are summarized based on the modeling of the specificity of the industrial control system and the attack methods. Based on a new abstract method of heterogeneous information, a heuristic industrial control system anomaly detection model based on combinatorial neural network is implemented. The test results show that the proposed model is more efficient, and the results are more accurate than the conventional intelligent methods.