Infrastructure security games

Infrastructure security against possible attacks involves making decisions under uncertainty. This paper presents game theoretic models of the interaction between an adversary and a first responder in order to study the problem of security within a transportation infrastructure. The risk measure used is based on the consequence of an attack in terms of the number of people affected or the occupancy level of a critical infrastructure, e.g. stations, trains, subway cars, escalators, bridges, etc. The objective of the adversary is to inflict the maximum damage to a transportation network by selecting a set of nodes to attack, while the first responder (emergency management center) allocates resources (emergency personnel or personnel-hours) to the sites of interest in an attempt to find the hidden adversary. This paper considers both static and dynamic, in which the first responder is mobile, games. The unique equilibrium strategy pair is given in closed form for the simple static game. For the dynamic game, the equilibrium for the first responder becomes the best patrol policy within the infrastructure. This model uses partially observable Markov decision processes (POMDPs) in which the payoff functions depend on an exogenous people flow, and thus, are time varying. A numerical example illustrating the algorithm is presented to evaluate an equilibrium strategy pair.     

Probabilistic programming models for traffic incident management operations planning

This paper proposes mathematical programming models with probabilistic constraints in order to address incident response and resource allocation problems for the planning of traffic incident management operations. For the incident response planning, we use the concept of quality of service during a potential incident to give the decision-maker the flexibility to determine the optimal policy in response to various possible situations. An integer programming model with probabilistic constraints is also proposed to address the incident response problem with stochastic resource requirements at the sites of incidents. For the resource allocation planning, we introduce a mathematical model to determine the number of service vehicles allocated to each depot to meet the resource requirements of the incidents by taking into account the stochastic nature of the resource requirement and incident occurrence probabilities. A detailed case study for the incident resource allocation problem is included to demonstrate the use of proposed model in a real-world context. The paper concludes with a summary of results and recommendations for future research.