基于证据推理和信念规则的工业控制系统的安全态度评估
Huishan Song1, Yanbin Yuan2, Yuhe Wang2
1School of Sports Science, Harbin Normal University, Harbin 150025, China.
Sensors (Basel, Switzerland)
|November 27, 2024
概括
本研究引入了一种新的安全评估模型,用于工业控制系统 (ICS),使用基于证据的推理和信念规则. 该模型提高了评估ICS安全性的准确性,解决了工业生产可持续性的数据不确定性.
科学领域:
- 计算机科学 计算机科学
- 工业工程 工业工程 工业工程
- 网络安全 网络安全
背景情况:
- 工业控制系统 (ICS) 越来越多地连接到互联网,提高效率,但引入安全漏洞.
- 确保工业生产的可持续性需要强大的ICS安全性.
- 数据的不确定性和专家知识的可靠性在ICS安全评估中带来了挑战.
研究的目的:
- 为工业控制系统 (ICS) 开发一种新的安全评估模型.
- 通过解决数据不确定性,提高ICS安全评估的准确性和可靠性.
- 为评估工业控制网络的安全状况提供一个框架.
主要方法:
- 使用证据推理 (ER) 来融合安全评估的各种影响因素.
- 使用专家定义的参数的信念规则基础构建评估框架.
- 整合一个混乱的映射适应性鱼优化算法来完善专家知识和提高准确性.
主要成果:
- 拟议的模型有效地将ICS中的各种信息整合起来,以进行准确的安全评估.
- 与现有模型相比,该模型在ICS安全评估中表现优越.
- 实验验证证了该模型在评估工业控制网络安全状况方面的有效性.
结论:
- 新的安全评估模型在保护工业控制系统方面取得了重大进展.
- 结合证据推理和自适应优化,提高了ICS安全评估的稳定性.
- 这种方法有助于确保工业生产的持续运行和可持续性.
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