Song Huishan, Yuan Yanbin, Wang Yuhe, Yang Jianbai, Luo Hang, Li Shiming
School of Sports Science, Harbin Normal University, Harbin 150025, China.
School of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China.
Sensors (Basel). 2024 Nov 6;24(22):7135. doi: 10.3390/s24227135.
With the rapid advancements in information technology and industrialization, the sustainability of industrial production has garnered significant attention. Industrial control systems (ICS), which encompass various facets of industrial production, are deeply integrated with the Internet, resulting in enhanced efficiency and quality. However, this integration also introduces challenges to the continuous operation of industrial processes. This paper presents a novel security assessment model for ICS, which is based on evidence-based reasoning and a library of belief rules. The model consolidates diverse information within ICS, enhancing the accuracy of assessments while addressing challenges such as uncertainty in ICS data. The proposed model employs evidential reasoning (ER) to fuse various influencing factors and derive security assessment values. Subsequently, a belief rule base is used to construct an assessment framework, grounded in expert-defined initial parameters. To mitigate the potential unreliability of expert knowledge, the chaotic mapping adaptive whale optimization algorithm is incorporated to enhance the model's accuracy in assessing the security posture of industrial control networks. Finally, the model's effectiveness in security assessment was validated through experimental results. Comparative analysis with other assessment models demonstrates that the proposed model exhibits superior performance in ICS security assessment.
随着信息技术和工业化的快速发展，工业生产的可持续性受到了广泛关注。涵盖工业生产各个方面的工业控制系统（ICS）与互联网深度融合，提高了效率和质量。然而，这种融合也给工业过程的持续运行带来了挑战。本文提出了一种基于证据推理和信念规则库的新型工业控制系统安全评估模型。该模型整合了工业控制系统中的各种信息，提高了评估的准确性，同时应对了工业控制系统数据不确定性等挑战。所提出的模型采用证据推理（ER）来融合各种影响因素并得出安全评估值。随后，使用信念规则库构建一个基于专家定义的初始参数的评估框架。为了减轻专家知识的潜在不可靠性，引入了混沌映射自适应鲸鱼优化算法，以提高模型评估工业控制网络安全态势的准确性。最后，通过实验结果验证了该模型在安全评估中的有效性。与其他评估模型的对比分析表明，所提出的模型在工业控制系统安全评估中表现出卓越的性能。
