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Determining and sharing risk data in distributed interdependent systems

Burnap, Peter, Cherdantseva, Yulia, Blyth, Andrew, Eden, Peter, Jones, Kevin, Soulsby, Hugh and Stoddart, Kristan 2017. Determining and sharing risk data in distributed interdependent systems. IEEE Computer 50 (4) , pp. 72-79. 10.1109/MC.2017.108

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Abstract

While the risks induced by system dependencies have been studied; little is known about modelling complex collections of supposedly independent systems at different geographical locations, which are in reality interdependent due to sharing often-unrecognized common elements. It could be argued that any risk analysis of a large infrastructure that does not take account of such interdependencies is dangerously introspective. We present a top-down, goal-to-dependencies approach to modelling and understanding such Complex Systems, which uses secure, distributed computing protocols to share risk data between the risk models of interdependent systems. We present a Bayesian-sensitivity measure of risk, which is both intuitively satisfying and accords with everyday notions of risk. The core benefit of this approach is to capture dependencies between systems and share risk data such that failure of an entity along the ‘supply chain’ can be rapidly propagated to those who depend on it allowing them to calculate the likely impact and respond accordingly.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Data Innovation Research Institute (DIURI)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: IEEE
ISSN: 0018-9162
Funders: Airbus Endeavr Wales
Last Modified: 02 Aug 2017 09:52
URI: http://orca.cf.ac.uk/id/eprint/103175

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