Assessment of Network Security Situation of Industrial Control System Based on CG-ELM

This paper proposes a network security situation assessment model of the industrial control system, and the model divides the industrial control network security situation assessment into two subtasks: threat traffic detection and determination of hierarchical weight. The purpose of threat traffic detection is to detect possible network attacks in network data traffic. In order to identify network attacks quickly and accurately, this paper uses the extreme learning machine model to classify network attacks, and uses the conjugate gradient method to improve the training efficiency of the extreme learning machine model. For the purpose of assessing the impact of different network attacks on the security situation of industrial control systems, this paper proposes a hierarchical industrial control network model for situation assessment based on the Analytic Hierarchy Process. The experimental verification of the situation assessment is carried out on the simulation platform of the sewage treatment industrial control system.