Alshammari, Kaznah, Beach, Thomas ORCID: https://orcid.org/0000-0001-5610-8027 and Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400 2021. Industry engagement for identification of cybersecurity needs practices for digital twins. Presented at: 2021 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), Cardiff, Wales, 21-23 June 2021. 2021 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC). IEEE, pp. 1-7. 10.1109/ICE/ITMC52061.2021.9570208 |
Abstract
Cyber-Physical Systems (CPS) are helping to make smart cities a reality, thanks to technological advancements in the construction industry. Through use of Information Communication Technologies (ICT), CPS integrates information and the physical world. Integrating Building Information Models (BIM) with IoT and sensor using CPS is becoming a more common goal in the industry. The adoption of digital twins in the future will open up new opportunities for CPS using tracking, simulation, and optimization strategies. Researchers, on the other hand, often overlook the cybersecurity implications. Assimilation of BIM data and cybersecurity principles has been difficult so far, and as a result, cybersecurity has been neglected. Specifically, this research will address research question; What are the key cybersecurity needed practices of built environment stakeholders? To answer these questions, this paper will survey the research of adoption of the cyber-physical system and digital twins regarding the industry. and determine obstacles to the adoption of cybersecurity for digital twins/CPS in the built environment. The findings of this study validated the value of using digital twins in industry. As a result, this paper assesses the use of digital twins in CPSs in order to determine the practices for bolstering cybersecurity and integrating digital twin and city standards in future urban cities.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering |
Publisher: | IEEE |
ISBN: | 9781665449632 |
ISSN: | 2693-8855 |
Last Modified: | 14 Dec 2022 02:25 |
URI: | https://orca.cardiff.ac.uk/id/eprint/145743 |
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