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Analyzing Cascading Effects among Critical Infrastructures
Stefan Schauer
Stefan Rass
Sandra König
Thomas Grafenauer
Martin Latzenhofer
Kees Boersma
Brian Tomaszeski
In this article, we present a novel approach, which allows not only to identify potential cascading effects within a network of interrelated critical infrastructures but also supports the assessment of these cascading effects. Based on percolation theory and Markov chains, our method models the interdependencies among various infrastructures and evaluates the possible consequences if an infrastructure has to reduce its capacity or is failing completely, by simulating the effects over time. Additionally, our approach is designed to take the intrinsic uncertainty into account, which resides in the description of potential consequences a failing critical infrastructure might cause, by using probabilistic state transitions. In this way, not only the critical infrastructure's risk and security managers are able to evaluate the consequences of an incident anywhere in the network but also the emergency services can use this information to improve their operation in case of a crisis and anticipate potential trouble spots.
urn:ISBN:978-0-692-12760-5
openurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fidl.iscram.org%2F&genre=proceeding&title=Analyzing%20Cascading%20Effects%20among%20Critical%20Infrastructures&stitle=Iscram%202018&issn=2411-3387&isbn=978-0-692-12760-5&date=2018&spage=428&epage=437&aulast=Stefan%20Schauer&au=Stefan%20Rass&au=Sandra%20K%F6nig&au=Thomas%20Grafenauer&au=Martin%20Latzenhofer&pub=Rochester%20Institute%20of%20Technology&place=Rochester%2C%20NY%20%28USA%29&sid=refbase%3AISCRAM
url:http://idl.iscram.org/show.php?record=2120
citekey:StefanSchauer_etal2018
citation:Stefan Schauer, Stefan Rass, Sandra König, Thomas Grafenauer, & Martin Latzenhofer. (2018). Analyzing Cascading Effects among Critical Infrastructures. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 428-437). Rochester, NY (USA): Rochester Institute of Technology.
2018
ConferencePaper
text
Cascading effects, interdependent critical infrastructures, Markov chains, simulation
file:http://idl.iscram.org/files/stefanschauer/2018/2120_StefanSchauer_etal2018.pdf
Rochester Institute of Technology
English
2411-3387
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management
2018
428
437
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