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Some Limitations Of 'risk = Threat × Vulnerability × Consequence' For Risk Analysis Of Terrorist Attacks

机译:恐怖袭击风险分析的“风险=威胁×脆弱性×结果”的局限性

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摘要

Several important risk analysis methods now used in setting priorities for protecting U.S. infrastructures against terrorist attacks are based on the formula: Risk = Threat × Vulnerability × Consequence. This article identifies potential limitations in such methods that can undermine their ability to guide resource allocations to effectively optimize risk reductions. After considering specific examples for the Risk Analysis and Management for Critical Asset Protection (RAMCAP~(TM) framework used by the Department of Homeland Security, we address more fundamental limitations of the product formula. These include its failure to adjust for correlations among its components, nonadditivity of risks estimated using the formula, inability to use risk-scoring results to optimally allocate defensive resources, and intrinsic subjectivity and ambiguity of Threat, Vulnerability, and Consequence numbers. Trying to directly assess probabilities for the actions of intelligent antagonists instead of modeling how they adaptively pursue their goals in light of available information and experience can produce ambiguous or mistaken risk estimates. Recent work demonstrates that two-level (or few-level) hierarchical optimization models can provide a useful alternative to Risk = Threat × Vulnerability × Consequence scoring rules, and also to probabilistic risk assessment (PRA) techniques that ignore rational planning and adaptation. In such two-level optimization models, defender predicts attacker's best response to defender's own actions, and then chooses his or her own actions taking into account these best responses. Such models appear valuable as practical approaches to antiterrorism risk analysis.
机译:目前用于确定优先级以保护美国基础设施免受恐怖袭击的几种重要的风险分析方法基于以下公式:风险=威胁×脆弱性×结果。本文确定了此类方法中的潜在限制,这些限制可能会破坏其指导资源分配以有效优化风险降低的能力。在考虑了国土安全部使用的关键资产保护风险分析和管理(RAMCAP〜TM)框架的特定示例之后,我们解决了产品公式的更多基本限制,包括其未能针对其组件之间的相关性进行调整,使用公式估算的风险的非可加性,无法使用风险评分结果来最佳地分配防御资源以及威胁,脆弱性和后果数的内在主观性和含糊性,试图直接评估智能对立者的行动概率而不是建模他们如何根据可用的信息和经验来适应性地实现目标,可能会产生模棱两可或错误的风险估计;最近的研究表明,两层(或几层)的层次优化模型可以为“风险=威胁×脆弱性×结果”提供有用的替代方法计分规则,以及概率风险评估(PRA)技术忽略了合理的计划和调整。在这样的两级优化模型中,防御者可以预测攻击者对防御者自己的行动的最佳反应,然后考虑这些最佳反应来选择攻击者自己的行动。这样的模型作为反恐风险分析的实用方法似乎很有价值。

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