Optimal and near-optimal resource allocation for transportation infrastructure protection

Abstract

The work proposed here will explore applications of game theory, optimization, and demonstrably near-optimal heuristics to modeling defense against security threats to networked transportation systems and to help in identifying optimal strategies for allocating resources among various possible defensive investments. The novel feature of the approach adopted here is the combined use of risk analysis methods with game theory and optimization methods to study management of intentional threats to networked transportation systems. The intent is to provide qualitative guidelines for optimal investment of resources to manage intentional threats to such systems. By contrast, much of the literature on security to date has not considered complex networked systems, often focusing on individual targets viewed as being independent of each other. Thus, we propose to extend and adapt the existing body of game-theoretic work on security to apply it to networked systems with complex series/parallel structures, which have not yet been addressed extensively in the literature. The results of this project will yield insights into the optimal defensive investments in networked transportation systems that yield the best tradeoff between the cost of the investments and the security of the resulting system.