2019
DOI: 10.1007/978-3-030-37670-3_5
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Aggregating Centrality Rankings: A Novel Approach to Detect Critical Infrastructure Vulnerabilities

Abstract: The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

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Cited by 4 publications
(3 citation statements)
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References 23 publications
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“…Another centrality-based method was proposed by Kay et al [9] to identify critical assets using a PageRank-based criticality score in the infrastructure network representing resource supplies between assets. On the contrary, Oliva et al [15] applied different perspectives from the degree, betweenness, eigenvector, and PageRank centrality measures to identify the most influential vertices in a network. However, in our opinion, it is worth adjusting the computation of centrality measures instead of adjusting their input or combining them.…”
Section: Network Centrality Measuresmentioning
confidence: 99%
“…Another centrality-based method was proposed by Kay et al [9] to identify critical assets using a PageRank-based criticality score in the infrastructure network representing resource supplies between assets. On the contrary, Oliva et al [15] applied different perspectives from the degree, betweenness, eigenvector, and PageRank centrality measures to identify the most influential vertices in a network. However, in our opinion, it is worth adjusting the computation of centrality measures instead of adjusting their input or combining them.…”
Section: Network Centrality Measuresmentioning
confidence: 99%
“…From a network topology perspective, node criticality is related to the location of the node in the network structure (Oliva et al, 2019). The most widely used analyses for measuring the criticality of nodes have been based on centrality measures (Rodrigues, 2019).…”
Section: Aba-closeness Vitalitymentioning
confidence: 99%
“…However, the adoption of a unique metric or indicator about the criticality rate of each node of the system is quite unrealistic due to the complex nature of the infrastructures. Two approaches able to consider multiple metrics with the aim to compute a final aggregated criticality holistic indicator are presented in [12,13]. The proposed approaches take into account multiple indicators based on multiple data source (topology data, field-related data, expert evaluations, etc.)…”
Section: Related Workmentioning
confidence: 99%