高含硫气田集输SCADA安全评估方法

doi:10.11885/j.issn.1674-5086.2023.11.07.01

摘要/Abstract

摘要： 油气能源基础设施安全越来越受到组织化攻击威胁，因此，对能源基础设施尤其是对高含硫气田集输 SCADA系统安全状态识别就显得尤为必要。为了揭示高含硫气田集输 SCADA 系统安全评估中随机性和不完全性对安全状态评估结果的影响，提出了基于云模型改进白化权函数的灰云安全评估方法。首先，对评估结果进行等级划分，设计了组合权重优化模型；然后，按照专家评分细则确定出样本矩阵，利用云模型改进白化权函数，形成灰色评估权矩阵；最后，结合优化后的权重通过逐级评估得到系统最终的风险值并确定系统风险评估状态。以 3 个实际应用场景为例，验证了方法的有效性。研究结果表明，与层次分析法、变异系数法、线性加权和乘法加权法比较，组合优化赋权方法的离散度为 0.456，线性加权和乘法加权的离散度为 0.514 和 0.860，层次分析法和变异系数法的离散度为 1.294 和 1.225，提出的组合优化赋权模型的离散度最小，表明此方法比其他方法更有效；将 SCADA 安全评估中风险指标信息不完全性与专家知识的不完全性和随机性结合起来，不仅能定性评估和预测整体 SCADA 系统的安全状态，而且实现二级指标风险量化；该模型能揭示各风险指标的脆弱程度，为下一步安全加固提供方向。本研究不仅有利于识别高含硫气田SCADA 系统安全状态，而且为其他行业安全评估提供了参考。

关键词: SCADA, 高含硫气田, 安全风险评估, 云模型, 层次分析法

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

中图分类号:

TE86

杨力, 秦红梅, 谢添一, 耿新宇. 高含硫气田集输SCADA安全评估方法[J]. 西南石油大学学报(自然科学版), 2024, 46(3): 117-129.

YANG Li, QIN Hongmei, XIE Tianyi, GENG Xinyu. Intelligent Security Assessment of Gathering and Transportation SCADA System in High Sulfur Gas Field[J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2024, 46(3): 117-129.

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