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Aggregating Centrality Rankings: A Novel Approach to Detect Critical Infrastructure Vulnerabilities

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11777)

Abstract

Assessing critical infrastructure vulnerabilities is paramount to arrange efficient plans for their protection. Critical infrastructures are network-based systems hence, they are composed of nodes and edges. The literature shows that node criticality, which is the focus of this paper, can be addressed from different metric-based perspectives (e.g., degree, maximal flow, shortest path). However, each metric provides a specific insight while neglecting others. This paper attempts to overcome this pitfall through a methodology based on ranking aggregation. Specifically, we consider several numerical topological descriptors of the nodes’ importance (e.g., degree, betweenness, closeness, etc.) and we convert such descriptors into ratio matrices; then, we extend the Analytic Hierarchy Process problem to the case of multiple ratio matrices and we resort to a Logarithmic Least Squares formulation to identify an aggregated metric that represents a good tradeoff among the different topological descriptors. The procedure is validated considering the Central London Tube network as a case study.

Keywords

Critical infrastructures Criticality analysis Ranking aggregation Analytic Hierarchy Process Least squares optimization 

Notes

Acknowledgements

This work was supported by INAIL via the European Saf€ra project “Integrated Management of Safety and Security Synergies in Seveso Plants” (4STER).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University Campus Biomedico of RomeRomeItaly
  2. 2.Centre for Logistics and Heuristic Optimisation (CLHO), Kent Business SchoolUniversity of KentCanterburyEngland
  3. 3.Sasin School of ManagementChulalongkorn UniversityBangkokThailand
  4. 4.University College DublinDublinIreland

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