Analysis and statistical properties of critical infrastructure interdependency multiflow models

Critical infrastructures such as the electric grid, oil and gas pipelines, telecommunications, and financial ser-vices are characterized by direct and transitive interdependencies which, owing to their complexity and the scale at which these occur, are not readily visible. Moreover, vulnerabilities in elements of the infrastructure can lead to cascading and cyclical failures only after some delay or as a result of feedback cycles in the infrastructure. In this paper we therefore describe several statistical and algorithmic approaches for the analysis of infrastructure interdependencies which can take into account not only abstract inter dependencies but also selected properties of infrastructure types such as buffering of resources. Based on a multigraph model we analyze the interactions of random failures and targeted attacks and use graph statistics to identify critical components in infrastructure topologies, thereby providing a mechanism for the development of more robust infrastructures and more effective allocation of defensive capabilities for existing critical infrastructure.