On the Effectiveness of Security Countermeasures for Critical Infrastructures

Abstract

A game-theoretic model is developed where an infrastructure of N targets is protected against terrorism threats. An original threat score is determined by the terrorist's threat against each target and the government's inherent protection level and original protection. The final threat score is impacted by the government's additional protection. We investigate and verify the effectiveness of countermeasures using empirical data and two methods. The first is to estimate the model's parameter values to minimize the sum of the squared differences between the government's additional resource investment predicted by the model and the empirical data. The second is to develop a multivariate regression model where the final threat score varies approximately linearly relative to the original threat score, sectors, and threat scenarios, and depends nonlinearly on the additional resource investment. The model and method are offered as tools, and as a way of thinking, to determine optimal resource investments across vulnerable targets subject to terrorism threats.

Probabilistic Multiple Hazard Resilience Model of an Interdependent Infrastructure System

“…Most of the published research considers the optimization of postdisaster individual infrastructure system restoration by applying a variety of modeling approaches and focusing on different aspects of the restoration strategy. Examples include minimization of the power system's restoration time under hurricane events (Liu, Davidson, & Apanasovich, ; Nateghi, Guikema, & Quiring, ), maximization of power system resilience with different operations models (Alderson, Brown, & Carlyle, ), maximization of performance and minimization of a telecommunication system cost (Matisziw, Murray, & Grubesic, ), and maximization of resource efficiency in spatially distributed networks (Hausken & He, ; Kroshl, Sarkani, & Mazzuchi, ). The joint restoration strategy work mostly considers a single‐layer infrastructure network resilience (Ouyang & Wang, ).…”

Sequential Hazards Resilience of Interdependent Infrastructure System: A Case Study of Greater Toronto Area Energy Infrastructure System

“…Most of the published research deals with the optimization of postdisaster individual infrastructure system restoration, applying a variety of modeling approaches and focusing on different aspects of the restoration strategy. Examples include: minimization of the power system's restoration time under hurricane event (Liu, Davidson, & Apanasovich, ; Nateghi, Guikema, & Quiring, ), maximization of power system resilience with different operations models (Fang et al., ), maximization of performance and minimization of a telecommunication system cost (Zobel, ), maximization of resource efficiency in spatially distributed networks (Hausken & He, ; Hosseini et al., ), and others. The joint restoration strategy work mostly considers single‐layer infrastructure network resilience.…”

“…Mass instantaneous infrastructure damage caused by natural hazards, such as hurricanes, earthquakes, and floods, could result in devastating, widespread, and often unpredictable impacts (Baroud, Barker, Ramirez‐Marquez, & Rocco, ). This leads to the need for more resilient infrastructure systems, able to function in a complex and volatile environment (Hausken & He, ).…”

Iterative selection of countermeasures for intelligent threat agents

“…The Haruspex suite adopts a distinct approach as it aims to reduce the probability that some agents reach their goals rather than diverting the agents to a distinct target . Hausken and He adopt a game theory framework to determine how to protect alternative targets of an attacker. Instead, we focus on how to minimize the investment to protect a single target.…”