A Measure for Resilience of Critical Infrastructures

König, Sandra; Schaberreiter, Thomas; Raß, Stefan; Schauer, Stefan

doi:10.1007/978-3-030-05849-4_5

Cited by 3 publications

(3 citation statements)

References 23 publications

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“…To conclude, within the plethora of the "current" existing tools (e.g. those presented or reviewed in [25,[37][38][39][40][41][42] or [43]), that all can simulate different resilience aspects of large and complex systems and/or apply optimization techniques to improve it (e.g. by indicating the optimum path towards system recovery or improving preparedness to unknowns) the approach presented here proposes a pragmatic and flexible way to achieve improvement through applying resilience indicators.…”

Section: Discussionmentioning

confidence: 99%

Resilience and Situational Awareness in Critical Infrastructure Protection: An Indicator-Based Approach

Jovanović¹,

Chakravarty²,

Jelić³

2021

Issues on Risk Analysis for Critical Infrastructure Protection

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The paper proposes a concept enabling quantitative assessment of resilience in critical entities developed in the European projects SmartResilience and InfraStress. The concept aims at combining simple communication-related advantages of simplified assessments results (such as “resilience very high” or “resilience very low”) with the advantages of the in-depth assessments (e.g. analysis of multiple sensor data). The paper describes the main elements of the innovative, indicator-based concept, starting with the “resilience cube” at the top, and continuing with the multi-level, hierarchical, indicator-based assessment methodology. The concept allows analyzing and assessing different aspects of practical resilience management. One can assess the resilience level of an entity at a given point in time, monitor their resilience level over time and benchmark it. One can also model and analyze the functionality of a system during a particular (threat) scenario, as well as stress-test it. The same methodology allows to optimize investment in improving resilience (e.g. in further training, in equipment, etc.), in a transparent and intuitive way. A resilience indicator database (over 4,000 indicators available) and a suite of tools (primarily developed within SmartResilience and InfraStress projects) and a repository of over 20 application cases and 300 scenarios, support application of the methodology. The concept has been discussed and agreed with over 50 different organizational stakeholders and is being embedded into the new ISO 31050 standard currently under development. Its “life-after-the-project” will be ensured by the dedicated “resilience rating initiative (ERRA)”. Although the concept and the tool in the form of the “ResilienceTool” were developed primarily for the resilience assessment of critical infrastructure (the “smart” ones in particular), they can be used for resilience assessment of other systems and through the extension of the, already initiated, implementation of AI techniques (machine learning) to make the ResilienceTool even more versatile and easier to use in the future.

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Section: Discussionmentioning

confidence: 99%

Resilience and Situational Awareness in Critical Infrastructure Protection: An Indicator-Based Approach

Jovanović¹,

Chakravarty²,

Jelić³

2021

Issues on Risk Analysis for Critical Infrastructure Protection

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“…[44], cyber and/or physical attacks [47]- [49], [51], [55], etc. Some research works concentrate on a type of asset whatever its granularity (healthcare [44], civil aviation [46], power systems [50], [51], [53], [56], port infrastructure [48], airport infrastructure [57], supply chain [56], ADS-B system [46], etc.). However, to our knowledge, no research work is dedicated to the definition of an approach for cyber or physical incident propagation in a healthcare infrastructure as a whole.…”

Section: B Incident Propagation Models and Approachesmentioning

confidence: 99%

“…Ref. [48] also chooses a dependency graph to represent interrelations between assets of the same critical infrastructure. To simulate the behavior of physical and cyber assets after an incident, it proposes to model assets (nodes of the graph) as a probabilistic automaton.…”

Section: B Incident Propagation Models and Approachesmentioning

confidence: 99%

Semantic-Based Approach for Cyber-Physical Cascading Effects Within Healthcare Infrastructures

et al. 2022

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This paper presents a framework for integrated cyber-physical security propagation study within critical infrastructures (hospitals use case). The framework includes an ontology for the semantic modeling of cyber-physical security. The impact propagation approach relies on propagation rules inferring the cascading effects of security incidents occurring in hospitals. An impact score module allows evaluating impacts' severity, considering implemented protection measures. This work is part of the European project SAFECARE, which provides a set of tests and demonstration sessions in partnership with 3 hospitals in Europe. During these tests, we measured effectiveness and efficiency metrics, as well as end users' satisfaction feedback. Experiments performed on real attack scenarios, show high effectiveness rates and a common agreement from end-users about the added value of the solution to enhance risks analysis practice and increase hospitals mitigation strategies efficiency.

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Real-time hierarchical predictive risk assessment at the national level: Mutually agreed predicted service disruption profiles

Malinowski¹,

Karbowski²

2020

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A Measure for Resilience of Critical Infrastructures

Cited by 3 publications

References 23 publications

Resilience and Situational Awareness in Critical Infrastructure Protection: An Indicator-Based Approach

Resilience and Situational Awareness in Critical Infrastructure Protection: An Indicator-Based Approach

Semantic-Based Approach for Cyber-Physical Cascading Effects Within Healthcare Infrastructures

Real-time hierarchical predictive risk assessment at the national level: Mutually agreed predicted service disruption profiles

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