Terrorism Scenario Identification by Superposition of Infrastructure Networks

Abstract

There is an emerging need for analysis of the risks of terrorism to the nation’s critical infrastructures, for which two aspects are relevant here. First, the process of risk assessment requires the identification and characterization of multiple terrorism scenarios. Second, infrastructure systems and terrorist organizations can be characterized as mathematical networks. This paper illuminates a relationship between superpositioned network models and the scenarios of risk to interdependent infrastructure systems as follows. An initial set of terrorism scenarios is identified based on interviews with domain experts. Direct, prima facie interactions of the scenarios and network components are identified across the superposition of networks. Indirect interactions of scenarios and network components are generated through modeling of various linkages across network components. Higher-order interactions correspond to multiple network components being associated with a terrorism scenario. The relationship of the terrorism scenarios with the superpositioned networks is thus studied by a combination of several interaction types (1) direct and indirect and (2) singular and higher order. Frequency analyses of the interactions among scenarios and the networks are developed to support refinement of the network models and the identified scenarios. An example with terrorism risks to oil pipeline and railway infrastructure is developed.