相互依存
弹性(材料科学)
组分(热力学)
脆弱性(计算)
概率逻辑
计算机科学
风险分析(工程)
脆弱性评估
贝叶斯网络
关键基础设施
可靠性工程
相互依存的网络
分布式计算
复杂网络
心理弹性
计算机安全
工程类
业务
人工智能
心理治疗师
法学
物理
万维网
心理学
热力学
政治学
标识
DOI:10.1080/23789689.2022.2126628
摘要
Critical infrastructure systems are complex and subjected to evolving risks and hazards, which makes anticipating their behavior difficult. To prioritize among actions that increase system resilience, it is critical to understand their impacts on parameters defining a network and on anticipated network performance. In this paper, the authors investigate the impacts of variations in three parameters on network vulnerability: component vulnerabilities, service interdependency redundancies, and system link configuration. The advances of this work compared to prior studies include: 1) The impacts of parameters varied across a range of values at the component level are evaluated considering component functionality and connectivity; 2) quantitative analyses of component performance as parameters vary are investigated based on system redundancies; and 3) probabilistic system interdependencies are analyzed through a Bayesian network that considers component pathways. Results quantify effects of changes in component vulnerabilities and dependencies and are used to discuss impacts on system resilience.
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