Abstract: In order to reveal the impact of randomness and incompleteness on the security status evaluation results of SCADA system in the high sulfur gas field, a grey cloud security evaluation method based on the improvement whitening weight function with cloud model is proposed. Firstly, the evaluation results were graded and a combination weight optimization model was designed. Then, a sample matrix was determined according to the expert scoring rules. The cloud model was used to improve the whitening weight function and calculate the grey evaluation weight matrix. Finally, the final risk value was obtained by the step-by-step evaluation formula and the system risk assessment status was determined. The effectiveness of the proposed method was verified in 3 accutal application scenarios. The results indicate that, compared with method of AHP, CV, LW and MWM, the discretization of the proposed combination optimization weighting method is 0.456, the discretization of MWM, CV, AHP and CV are 0.514, 0.860, 1.294, and 1.225 respectively. The proposed combination optimization weighting method has the smallest discretization, indicating that it is more effective than other methods. This model combines the incompleteness of risk indicator information in SCADA security assessment with the incompleteness and randomness of expert knowledge, which can not only qualitatively evaluate and predict the overall security status of the SCADA system, but also achieve the quantification of secondary indicator risk. This method can reveal the vulnerability level of various risk indicators and provide direction for the next step of safety reinforcement. The proposed method is not only conducive to identifying the security status of SCADA systems in high sulfur gas fields, but also provides a reference for security assessment in other industries.

Key words: SCADA, high sulfur gas fields, security risk assessment, cloud model, analytic hierarchy process