Improving the Cybersecurity of Critical National Infrastructure using Modelling and Simulation

作     者：Ani, Uchenna D. McK Watson, Jeremy D. Tuptuk, Nilufer Hailes, Steve Carr, Madeline Maple, Carsten 

作者机构：School of Computing and Mathematics Keele University United Kingdom Department of Science Technology Engineering and Public Policy University College London United Kingdom Department of Security and Crime Science University College London United Kingdom Department of Computer Science University College London United Kingdom Cybersecurity Centre WMG University of Warwick United Kingdom 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2022年

核心收录：

主　　题：Critical infrastructures 

摘      要：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. This policy briefing is targeted at government departments and agencies with management and regulatory roles linked to critical infrastructure sectors listed above. The advice may be particularly relevant to DfT, Cabinet Office, BEIS, Home Office, DCMS, DEFRA, and GO-Science. © 2022, CC BY.