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Title	Digital Twin In Healthcare: Security Threat Meta-Model
ID_Doc	20206
Authors	Karakra A.; Fontanili F.; Taweel A.; Lamine E.; Lamothe J.; Barghouthi H.
Year	2022
Published	Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, 2022-December
DOI	http://dx.doi.org/10.1109/AICCSA56895.2022.10017729
Abstract	A virtual mirrored replica of the real-world, has become a new trend in recent years with the advent of Industry 4.0, shows how intelligent digital twins (DT) can unlock busi-ness value. The implementation of DT requires various types of technologies, including the Internet of Things (IoT), cloud computing, artificial intelligence, and others. Today, DTs can be used in various fields, including manufacturing, smart cities and healthcare. It can be used to monitor the real environment, predict its future, control its behavior, and improve its overall performance. Despite the aforementioned advantages of DTs, if not protected, they can also be considered as an open environment for attackers. If attackers take over a DT, they may end up owning the real environment controlled by the DT. This can result in damaging consequences. This paper explores the potential security and privacy threats that may be brought in through DTs. It proposes and presents a threat meta-model of DTs that identifies key security aspects of concern. © 2022 IEEE.
Author Keywords	Digital Twin; Healthcare; Real World; Security; Virtual World

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