Some Limitations of "Risk = Threat x Vulnerability x Consequence" for Risk Analysis of Terrorist Attacks
Some Limitations of "Risk = Threat x Vulnerability x Consequence" for Risk Analysis of Terrorist Attacks
复制标题
DOI：
10.1111/j.1539-6924.2008.01142.x
复制
发表时间：
2008-12-01
期刊：
影响因子：
3.8
通讯作者：
Cox, Louis Anthony (Tony), Jr.
中科院分区：
文献类型：
--
作者：
Cox, Louis Anthony (Tony), Jr.
目前，在确定保护美国基础设施免受恐怖袭击的优先次序时，使用的几种重要的风险分析方法都是基于以下公式：风险=威胁×脆弱性×后果。本文确定了这些方法的潜在局限性，这些局限性可能会破坏它们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））框架的具体例子后，我们解决了产品公式的更基本的限制。这些问题包括未能调整其组成部分之间的相关性，使用公式估计的风险的不可加性，无法使用风险评分结果来优化分配防御资源，以及威胁，脆弱性和后果数字的内在主观性和模糊性。试图直接评估智能对手行动的可能性，而不是根据可用信息和经验对他们如何自适应地追求目标进行建模，可能会产生模糊或错误的风险估计。最近的工作表明，两级（或几级）分层优化模型可以提供一个有用的替代风险=威胁×脆弱性×后果评分规则，也概率风险评估（PRA）技术，忽略合理的规划和适应。在这种两级优化模型中，防御者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他或她自己的行动。这些模型作为反恐风险分析的实用方法似乎很有价值。
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 x Vulnerability x 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 x Vulnerability x 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.