Impact of Functional Models in a Decision Context of Critical Infrastructure Vulnerability
(2014) Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM2014)- Abstract
- Critical infrastructures provide essential services for the functioning of the society, and disruption of these services can lead to large-scale consequences. Hence, it is of utmost importance to analyze the vulnerability of critical infrastructures and use the results to guide decisions of improving their robustness towards strains. Since real-life critical infrastructures can be regarded as complex systems, such analyses can prove challenging. To analyze the system response of strains affecting the system, several different models have been suggested in the scientific literature. These range from simplistic static topological models to more advanced engineering models. The benefit of using more simplistic models is that they are... (More)
- Critical infrastructures provide essential services for the functioning of the society, and disruption of these services can lead to large-scale consequences. Hence, it is of utmost importance to analyze the vulnerability of critical infrastructures and use the results to guide decisions of improving their robustness towards strains. Since real-life critical infrastructures can be regarded as complex systems, such analyses can prove challenging. To analyze the system response of strains affecting the system, several different models have been suggested in the scientific literature. These range from simplistic static topological models to more advanced engineering models. The benefit of using more simplistic models is that they are computationally less burdensome and hence more comprehensive and explorative vulnerability studies can be carried out, with the downside that they might not accurately enough describe system performance. More advanced engineering models on the other hand capture the system performance more accurately, with the downside that they are computationally burdensome and hence less comprehensive studies can be carried out. Here the focus is on how different functional models impacts estimated effectiveness of improvement strategies in a decisions context from a vulnerability perspective. More precisely nine different functional models are used, from static network theoretical models to engineering models, to assess the vulnerability of a test system, the IEEE RTS96 transmission power system. The results from these analyses are then used in a decision context to identify critical components and for suggesting structural improvements of the system. The overarching questions is whether the use of different models will have an impact on the decision of which components are deemed most critical and what improvement strategies are ranked highest. Preliminary results suggest that the use of model impacts the decision, and hence care should be taken when using these models to inform decisions of critical infrastructure improvement. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3916628
- author
- Johansson, Jonas LU and Hassel, Henrik LU
- organization
- publishing date
- 2014
- type
- Contribution to conference
- publication status
- submitted
- subject
- keywords
- Critical Infrastructure, Vulnerability, Functional Models, Decision Making
- conference name
- Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM2014)
- conference location
- Liverpool, United Kingdom
- conference dates
- 2014-07-13 - 2014-07-16
- language
- English
- LU publication?
- yes
- id
- d6cc2fb1-86e8-4585-8877-5d7c8155ad89 (old id 3916628)
- date added to LUP
- 2016-04-04 14:38:13
- date last changed
- 2018-11-21 21:21:27
@misc{d6cc2fb1-86e8-4585-8877-5d7c8155ad89,
abstract = {{Critical infrastructures provide essential services for the functioning of the society, and disruption of these services can lead to large-scale consequences. Hence, it is of utmost importance to analyze the vulnerability of critical infrastructures and use the results to guide decisions of improving their robustness towards strains. Since real-life critical infrastructures can be regarded as complex systems, such analyses can prove challenging. To analyze the system response of strains affecting the system, several different models have been suggested in the scientific literature. These range from simplistic static topological models to more advanced engineering models. The benefit of using more simplistic models is that they are computationally less burdensome and hence more comprehensive and explorative vulnerability studies can be carried out, with the downside that they might not accurately enough describe system performance. More advanced engineering models on the other hand capture the system performance more accurately, with the downside that they are computationally burdensome and hence less comprehensive studies can be carried out. Here the focus is on how different functional models impacts estimated effectiveness of improvement strategies in a decisions context from a vulnerability perspective. More precisely nine different functional models are used, from static network theoretical models to engineering models, to assess the vulnerability of a test system, the IEEE RTS96 transmission power system. The results from these analyses are then used in a decision context to identify critical components and for suggesting structural improvements of the system. The overarching questions is whether the use of different models will have an impact on the decision of which components are deemed most critical and what improvement strategies are ranked highest. Preliminary results suggest that the use of model impacts the decision, and hence care should be taken when using these models to inform decisions of critical infrastructure improvement.}},
author = {{Johansson, Jonas and Hassel, Henrik}},
keywords = {{Critical Infrastructure; Vulnerability; Functional Models; Decision Making}},
language = {{eng}},
title = {{Impact of Functional Models in a Decision Context of Critical Infrastructure Vulnerability}},
year = {{2014}},
}