Affiliations: [a] School of Science, Jimei University, Xiamen, Fujian, P. R. China
| [b] Digital Fujian Big Data Modeling and Intelligent Computing Institute, School of Science, Jimei University, Xiamen, Fujian, P. R. China
Correspondence:
[*]
Corresponding author. Mozhong Zhu, School of Science, Jimei University, Xiamen, Fujian, 361021, P. R. China. E-mail: 1587304067@qq.com.
Abstract: Once industrial control systems are targeted by cyber-attacks, the consequences can be severe, including asset loss, environmental pollution, and public security risks. Risk assessment is an important way to ensure that industrial control systems operate efficiently, steadily and safely. The purpose of this paper is to develop a risk assessment model for industrial control systems based on asymmetric connection cloud and Choquet integral, which fully takes into account the fact that values of risk indicators are often fuzzy, random, asymmetrically distributed in finite intervals, and there are interactions among different indicators. To do so, we first establish a risk assessment index system to ensure the full reflection of availability, integrity, and confidentiality in the results of risk assessment for industrial control systems. Then we establish classification standards for each evaluation indicator based on the importance of assets, vulnerabilities, and threats in evaluating the risk of industrial control systems. Next we develop a risk assessment model based on asymmetric connection cloud and Choquet integral to determine the risk level of industrial control systems. In the following, an example is provided to demonstrate the feasibility and reliability of this proposed model. The experimental results have demonstrated a high level of credibility in assessing cyber-attacks by the proposed model, indicating its potential for analyzing the current security and risk posture of industrial control systems.
Keywords: Industrial control systems, risk assessment, asymmetric connection cloud, choquet integral
