Beyond Probabilistic Risk Assessment: Deterrence, Dynamic Threat, and Countermeasure Allocation in Transportation Hubs

• Activity Number: 172 - Risk Prediction and Analysis
• Type: Contributed
• Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
• Sponsor: Section on Risk Analysis
• Author(s): Craig Bakker* and Robert T Brigantic and Kellie J MacPhee and Nicholas J Betzsold and Daniel P McCabe and Casey J Perkins
• Companies: Pacific Northwest National Laboratory and Pacific Northwest National Laboratory and Pacific Northwest National Laboratory and Pacific Northwest National Laboratory and Pacific Northwest National Laboratory and Pacific Northwest National Laboratory
• Keywords: Risk Analysis; Counterterrorism; Game Theory; Deterrence Modelling

Abstract

Probabilistic Risk Assessment (PRA) methods calculate risk as the product of consequence, vulnerability, and threat. One could view this as a measurement of expected consequence, where threat is the probability of an adverse event happening and vulnerability is the probability of that adverse event resulting in a given quantified consequence. PRA typically treats threat as a static quantity, but that may not be a good assumption in a counterterrorism setting. In that setting, adversaries can be adaptive, and there is also the possibility of deterring those adversaries. Previously, we developed a PRA-like model for allocating security assets in transportation hubs to minimize the terrorism risk to those facilities. We have now extended our model to include probabilistic countermeasure assignments and dynamic threat in an attacker-defender game theory framework. Within this framework, we quantify countermeasure deterrence, model uncertainty tolerance (for the attacker or the defender), and account for the physical layout of the transportation facility.