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.
T. Service et al., "Infrastructure Hardening: A Competitive Co-evolutionary Methodology Inspired by Neo-Darwinian Arms Races," Proceedings of the 31st Annual International Computer Software and Applications Conference (COMPSAC'06) (2007, Beijing), Institute of Electrical and Electronics Engineers (IEEE), Jul 2007.
The definitive version is available at https://doi.org/10.1109/COMPSAC.2007.129
31st Annual International Computer Software and Applications Conference (COMPSAC'06) (2007: July 24-27, Beijing)
Keywords and Phrases
Coevolutionary Methodology; Infrastructure Hardening; Neo-Darwinian Arms Races; Cascading Failures; Combinatorial Complexity; Fault Tolerance
Article - Conference proceedings
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