Stochastic counterfactual risk analysis for the vulnerability assessment of cyber-physical attacks on electricity distribution infrastructure networks

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Pant, R 
Leverett, E 

In December 2015, a cyber-physical attack took place on the Ukrainian electricity distribution network. This is regarded as one of the first cyber-physical attacks on electricity infrastructure to have led to a substantial power outage and is illustrative of the increasing vulnerability of Critical National Infrastructure to this type of malicious activity. Few data points, coupled with the rapid emergence of cyber phenomena, has held back the development of resilience analytics of cyber-physical attacks, relative to many other threats. We propose to overcome data limitations by applying stochastic counterfactual risk analysis as part of a new vulnerability assessment framework. The method is developed in the context of the direct and indirect socio-economic impacts of a Ukrainian-style cyber-physical attack taking place on the electricity distribution network serving London and its surrounding regions. A key finding is that if decision-makers wish to mitigate major population disruptions, then they must invest resources more-or-less equally across all substations, to prevent the scaling of a cyber-physical attack. However, there are some substations associated with higher economic value due to their support of other Critical National Infrastructures assets which justifies the allocation of additional cyber security investment to reduce the chance of cascading failure. Further cyber-physical vulnerability research must address the trade-offs inherent in a system made up of multiple institutions with different strategic risk mitigation objectives and metrics of value, such as governments, infrastructure operators, and commercial consumers of infrastructure services.

Critical National Infrastructure, cyber-physical attack, infrastructure
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Risk Analysis
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Blackwell Publishing Inc.
EPSRC (via University of Oxford) (R38771/CN001 MISTRAL-AFR00560)
EO, RP, ST and JH were supported by the Engineering and Physical Sciences Research Council via the program grant Multi-scale Infrastructure Systems Analytics (Mistral) (EP/N017064/1).