Spotting criticalities in Critical Infrastructure networks is a crucial task in order to implement effective protection strategies against exogenous or malicious events. Yet, most of the approaches in the literature focus on specific aspects (e.g., presence of hubs, minimum paths) and there is a need to identify tradeoffs among importance metrics that are typically clashing with each other. In this paper we propose an approach for the assessment of criticalities which combines multi-criteria decision making techniques and topological/dynamical centrality measures. In particular, we resort to the Sparse Analytic Hierarchy Process (SAHP) technique to calculate the relevance of the different metrics based on pairwise comparisons of the metrics by Subject Matter Experts (SMEs) and to merge the different metrics into a holistic indicator of node criticality/importance that takes into account all the metrics. With the aim to experimentally demonstrate the potential of the proposed approach, we consider a case study related to the Central London Tube Network. According to the experimental results, the proposed aggregated ranking exhibits negligible correlation with the single metrics being aggregated, thus suggesting that the proposed approach effectively combines the different metrics into a new perspective.

Multi-criteria node criticality assessment framework for critical infrastructure networks

Faramondi L;Oliva G;Setola R
2020-01-01

Abstract

Spotting criticalities in Critical Infrastructure networks is a crucial task in order to implement effective protection strategies against exogenous or malicious events. Yet, most of the approaches in the literature focus on specific aspects (e.g., presence of hubs, minimum paths) and there is a need to identify tradeoffs among importance metrics that are typically clashing with each other. In this paper we propose an approach for the assessment of criticalities which combines multi-criteria decision making techniques and topological/dynamical centrality measures. In particular, we resort to the Sparse Analytic Hierarchy Process (SAHP) technique to calculate the relevance of the different metrics based on pairwise comparisons of the metrics by Subject Matter Experts (SMEs) and to merge the different metrics into a holistic indicator of node criticality/importance that takes into account all the metrics. With the aim to experimentally demonstrate the potential of the proposed approach, we consider a case study related to the Central London Tube Network. According to the experimental results, the proposed aggregated ranking exhibits negligible correlation with the single metrics being aggregated, thus suggesting that the proposed approach effectively combines the different metrics into a new perspective.
2020
Analytic hierarchy process; Centrality; Critical infrastructure protection
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/10453
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