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Integration of Cyber Security Frameworks, Models and Approaches for Building Design Principles for the Internet-of-Things in Industry 4.0

Radanliev, Petar and De Roure, David and Nurse, Jason R. C. and Nicolescu, Razvan and Huth, Michael and Cannady, Stacy and Montalvo, Rafael Mantilla (2018) Integration of Cyber Security Frameworks, Models and Approaches for Building Design Principles for the Internet-of-Things in Industry 4.0. In: Living in the Internet of Things: Cybersecurity of the IoT - 2018. IET. E-ISBN 978-1-78561-843-7. (doi:10.1049/cp.2018.0041) (KAR id:67464)

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Official URL:
http://dx.doi.org/10.1049/cp.2018.0041

Abstract

This research article reports the results of a qualitative case study that correlates academic literature with five Industry 4.0 cyber trends, seven cyber risk frameworks and two cyber risk models. While there is a strong interest in industry and academia to standardise existing cyber risk frameworks, models and methodologies, an attempt to combine these approaches has not been done until present. We apply the grounded theory approach to derive with integration criteria for the reviewed frameworks, models and methodologies. Then, we propose a new architecture for the integration of the reviewed frameworks, models and methodologies. We therefore advance the efforts of integrating standards and governance into Industry 4.0 and offer a better understanding of a holistic economic impact assessment model for IoT cyber risk.

Item Type: Book section
DOI/Identification number: 10.1049/cp.2018.0041
Uncontrolled keywords: Industry 4.0., Internet of Things, case study, cyber security framework
Subjects: Q Science
T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Jason Nurse
Date Deposited: 03 Jul 2018 19:20 UTC
Last Modified: 19 Nov 2022 22:22 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/67464 (The current URI for this page, for reference purposes)
Nurse, Jason R. C.: https://orcid.org/0000-0003-4118-1680
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