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A Methodology for Resilience Optimisation of Interdependent Critical Infrastructures

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Critical Information Infrastructures Security (CRITIS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9578))

Abstract

Many methodologies proposed in the literature for modelling and simulating the behaviour of critical infrastructures (CIs) in response to disruptive events are based on exhaustive analytic models, require extensive amounts of data and suffer from high computational burden. These factors restrain their applicability in practical policy making processes, which often require higher flexibility and efficiency in the delivery of analysis and prediction results. Taking these constraints into consideration, in this paper we propose a resilience-oriented framework for the high-level analysis of networked CIs, based on the concept of functional representation of interdependencies. We also show the usefulness of the proposed methodology to improve the operability of the network by appropriately tuning relevant parameters of selected assets according to an optimisation algorithm aiming at the improvement of the overall resilience of the CI network. This feature ultimately provides a guidance for selecting proper strategies to bound the propagation of damages across interdependent assets/infrastructures.

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    http://facies.dia.uniroma3.it.

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Acknowledgment

This work is supported by the Annual Work Programme 2010 and 2012 for the specific programme on the “Prevention, Preparedness and Consequence Management of Terrorism and other Security-related Risks (CIPS)”, which is financed by Directorate General Home Affairs of the European Commission. The authors would like to express their gratitude for this support.

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Correspondence to Luca Galbusera .

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Galbusera, L., Azzini, I., Giannopoulos, G. (2016). A Methodology for Resilience Optimisation of Interdependent Critical Infrastructures. In: Rome, E., Theocharidou, M., Wolthusen, S. (eds) Critical Information Infrastructures Security. CRITIS 2015. Lecture Notes in Computer Science(), vol 9578. Springer, Cham. https://doi.org/10.1007/978-3-319-33331-1_5

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  • DOI: https://doi.org/10.1007/978-3-319-33331-1_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33330-4

  • Online ISBN: 978-3-319-33331-1

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