The world is increasingly dependent on critical infrastructures such as the electric power grid, water, gas, and oil transport systems, which are susceptible to cascading failures that can result from a few faults. Due to the combinatorial complexity in the search spaces involved, most traditional search techniques are inappropriate for identifying these faults and potential protections against them. This paper provides a computational methodology employing competitive coevolution to simultaneously identify low-effort, high-impact faults and corresponding means of hardening infrastructures against them. A power system case study provides empirical evidence that our proposed methodology is capable of identifying cost effective modifications to substantially improve the fault tolerance of critical infrastructures.

Meeting Name

31st Annual International Computer Software and Applications Conference (COMPSAC'06) (2007: July 24-27, Beijing)


Computer Science

Keywords and Phrases

Coevolutionary Methodology; Infrastructure Hardening; Neo-Darwinian Arms Races; Cascading Failures; Combinatorial Complexity; Fault Tolerance

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 2007 Institute Electrical and Electronics Engineers, Inc., All rights reserved.

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