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Improving the Cybersecurity of Critical National Infrastructure using Modelling and Simulation

Ani, Uchenna D; Watson, Jeremy D; Tuptuk, Nilufer; Hailes, Steve; Carr, Madeline; Maple, Carsten; (2022) Improving the Cybersecurity of Critical National Infrastructure using Modelling and Simulation. PETRAS: London, UK. Green open access

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Abstract

This policy note aims to raise awareness of the importance of adopting cybersecurity modelling and simulation techniques that embody integrated social and technical factors. It is based on research and synthesis following a state-of-the-art literature survey and engagement workshop with critical infrastructure stakeholders hosted by the Department for Transport (DfT) in February 2019, and a desk-based study in the ongoing (2020-2022) PETRAS Modelling for Sociotechnical Security (MASS) project. Participants from academia, business and industrial sectors, and government came together to discuss the effectiveness of modelling and simulation to support the protection of modern Critical Infrastructure Systems. The discussion also covered how government effort, through policy interventions, can support the National Cyber Security Strategy 2016-2021, and beyond. Although the focus of the initial workshop was the transport sector, the insights drawn and recommendations made can be applied to other critical national infrastructure sectors such as Energy, Water, Defence, Chemicals, and Food.

Type: Report
Title: Improving the Cybersecurity of Critical National Infrastructure using Modelling and Simulation
Open access status: An open access version is available from UCL Discovery
Publisher version: https://www.ucl.ac.uk/steapp/research/digital-tech...
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science
URI: https://discovery.ucl.ac.uk/id/eprint/10201618
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