| Title | Information Security Risk Assessment of Industrial Control System Based on Hybrid Genetic Algorithms |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Jie, Chen |
| Conference Name | 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) |
| Keywords | Automation, control systems, evidence theory, Hierarchy, hybrid genetic algorithm, industrial control, industrial control system, industrial control systems, Information security, measurement uncertainty, Mechatronics, pubcrawl, Resiliency, Scalability, scalable systems, security risk assessment |
| Abstract | In order to solve the problem of quantitative assessment of information security risks in industrial control systems, this paper proposes a method of information security risk assessment for industrial control systems based on modular hybrid genetic algorithm. Combining with the characteristics of industrial control systems, the use of hybrid genetic algorithm evidence theory to identify, evaluate and assess assets and threats, and ultimately come to the order of the size of the impact of security threats on the specific industrial control system information security. This method can provide basis for making decisions to reduce information security risks in the control system from qualitative and quantitative aspects. |
| DOI | 10.1109/ICMTMA52658.2021.00097 |
| Citation Key | jie_information_2021 |
Information Security Risk Assessment of Industrial Control System Based on Hybrid Genetic Algorithms