Preliminary Interdependency Analysis: An Approach to Support Critical Infrastructure Risk Assessment

Bloomfield, R. E., Popov, P. T., Salako, K., Stankovic, V. & Wright, D. (2017). Preliminary Interdependency Analysis: An Approach to Support Critical Infrastructure Risk Assessment. Reliability Engineering and System Safety, doi: 10.1016/j.ress.2017.05.030

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We present a methodology, Preliminary Interdependency Analysis (PIA), for analysing interdependencies between critical infrastructure (CI). Consisting of two phases – qualitative analysis followed by quantitative analysis – an application of PIA progresses from a relatively quick elicitation of CI-interdependencies to the building of representative CI models, and the subsequent estimation of any resilience, risk or criticality measures an assessor might be interested in. By design, stages in the methodology are both flexible and iterative, resulting in interacting CI models that are scalable and may vary significantly in complexity and fidelity, depending on the needs and requirements of an assessor. For model parameterisation, one relies on a combination of field data, sensitivity analysis and expert judgement. Facilitated by dedicated software tool support, we illustrate PIA by applying it to a complex case-study of interacting Power (distribution and transmission) and Telecommunications networks in the Rome area. A number of studies are carried out, including: 1) an investigation of how “strength of dependence” between the CIs’ components affects various measures of risk and uncertainty, 2) for resource allocation, an exploration of different, but related, notions of CI component importance, and 3) highlighting the impact of model fidelity on the estimated risk of cascades.

Publication Type: Article
Additional Information: © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Publisher Keywords: Interdependency Analysis; Risk Assessment; Cascading failure; Critical Infrastructure Resilience
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Informatics > Centre for Software Reliability

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