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AI-enabled Adaptive PHY-Layer Authentication for Integrated TN-NTN IoT-5G Healthcare
University West, Department of Engineering Science, Division of computer engineering and computer science. Kristianstad University (SWE). (Datateknik)
The University of New South Wales, Graduate School of Biomedical Engineering, Sydney (AUS).
Norweigan Computing Center, Oslo (NOR).
Kristianstad University, Department of Computer Science (SWE).
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2026 (English)In: 2026 IEEE International Conference on Communications Workshops, ICC Workshops 2026 - Proceedings, 2026, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

The combined terrestrial network (TN) and Non-terrestrial Networks (NTN) with satellite and UAV-driven Communication is the crtical and major role player for the pervasive and reliable connectivity. Fifth Generation (5G) empowers and revolutionizes the IoT by enhancing and extending the connectivity between portable devices for supporting various applications for instance, healthcare, smart cities, and hospital management. Due to diverse and profound impact of the IoT there are various potential benefits in parallel with the insightful challenges. The heterogenous platform, diverse connectivity, and dynamic features of IoT-5G there are more risks and security vulnerabilities by intruders and attackers. In addition, security particularly authentication is the paramount for implementation, management, and monitoring of the IoT and 5G platforms. A joint adaptive, continuous and reliable (ACR) mechanism for IoT-5G authentication is in demand to be developed. Due to heterogenous technological trends, and lack of uniform interoperable standard and solution, and restricted computing and networking capacity of IoT devices there is need of lightweight and adaptive, continuous, reliable and authenticated data exchange solution. Up to now there are less efforts from research community dedicated to developing an adaptive solution with lower-latency fast and continuous authentication, and high reliability to IoT-5G by adopting the PHY-layer parameters. Our proposed ACR authentication mechanism follows the multi-authentication behavior with soft notion of trust instead of hard flag of binary sequences. Moreover, we aim to detect the intruders with suspicious behavior at PHY-layer, because it is difficult to prevent the access of such illegitimate entities to higher layers.

Place, publisher, year, edition, pages
2026. p. 1-6
Keywords [en]
Adaptive and continuous authentication; AI-enabled authentication; Healthcare; IoT-5G; PHY-layer security; TN-NTN
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:hv:diva-25796DOI: 10.1109/iccworkshops63917.2026.11586499Scopus ID: 2-s2.0-105045579445ISBN: 9798331576240 (electronic)ISBN: 9798331576257 (print)OAI: oai:DiVA.org:hv-25796DiVA, id: diva2:2094092
Conference
2026 IEEE International Conference on Communications Workshops, ICC Workshops 2026, Glasgow, United Kingdom, 24 May 2026 - 28 May 2026
Available from: 2026-08-20 Created: 2026-08-20 Last updated: 2026-08-20

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Sodhro, Ali HassanDjebbar, Fatiha

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