Critical infrastructure dependency assessment using the input–output inoperability model

Setola, Roberto; Porcellinis, Stefano De; Sforna, M.

doi:10.1016/j.ijcip.2009.09.002

Cited by 149 publications

(75 citation statements)

References 10 publications

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“…For example, Carreras et al (2012) have conducted statistical studies of blackouts that enable the identification of critical power lines or groups of power lines for a given network model to identify lines likely to trigger or propagate cascading effects due to power line vulnerabilities. Setola et al (2009) approach also use FL to minimise the uncertainty and ambiguity associated with subjective information received from domain experts. On the other hand, our methodology combines FL with various time growth models.…”

Section: Comparison With Other Approachesmentioning

confidence: 99%

A process-based dependency risk analysis methodology for critical infrastructures

Stergiopoulos

Kouktzoglou

Theocharidou

et al. 2017

IJCIS

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This paper applies research in dependency modelling to a process-based risk assessment methodology suitable for critical infrastructures. The proposed methodology dynamically assesses the evolution of cascading failures over time between assets involved in a business process of an infrastructure. This approach can be applied by a CI operator/owner to explore how a failure in a single component (asset) affects the other assets and relevant business processes. It could also be applied in an analysis that includes multiple CI operators in the same supply chain to explore the dependencies between their assets and explore how these affect the provision of key societal services. The paper presents a proof-of-concept tool, based on business-process risk assessment and graph modelling, and a realistic case example of a rail scheduling process. The approach allows risk assessors and decision makers to analyse and identify critical dependency chains and it can reveal underestimated risks due to dependencies.Keywords: risk assessment; business process; asset; dependency; cascading failures; risk chains; likelihood; impact; critical infrastructure. A process-based dependency risk analysis methodology 185Reference to this paper should be made as follows: Stergiopoulos, G., Kouktzoglou, V., Theocharidou, M. and Gritzalis, D. (2017) 'A process-based dependency risk analysis methodology for critical infrastructures', Int.

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Section: Comparison With Other Approachesmentioning

confidence: 99%

A process-based dependency risk analysis methodology for critical infrastructures

Stergiopoulos

Kouktzoglou

Theocharidou

et al. 2017

IJCIS

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“…However, as illustrated in [32] such indices refer only to the direct influence exerted or suffered by each infrastructure. In other terms, those indices do not consider the consequences of second or higher order interdependencies, i.e.…”

Section: Holistic Approachesmentioning

confidence: 99%

“…Often for the discrete-time interdependency model one can directly assess the values of the elements of matrix A for example via interview with sectors' experts [33,32].…”

Section: Holistic Approachesmentioning

confidence: 99%

Modelling Dependencies Between Critical Infrastructures

Setola

Theocharidou

2016

Studies in Systems, Decision and Control

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“…Many approaches have been used to model infrastructure interaction including for example, agent-based models , input-output models (Setola 2009), neural networks (Min and Duenas-Osorio, 2009) and scalable multi-graph methods (Svendsen and Wolthusen, 2007). As well as differing in their general approach, these methods differ widely in the type, size and number of networks being considered.…”

Section: Introductionmentioning

confidence: 99%

“…One notable example of agent-based modeling applied to the area of interdependent infrastructure is the Critical Infrastructure Modeling Software (CIMS) developed by a group at the Idaho National Laboratory . Input-output inoperability models (IIM) are financial models that have been used for analyzing the cascading effects in critical infrastructure systems (Setola et al, 2009). IIM uses inoperability levels to describe the state of each infrastructure network.…”

Section: Introductionmentioning

confidence: 99%