Secure-fault-tolerant efficient industrial internet of healthcare things framework based on digital twin federated fog-cloud networks

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dc.contributor.authorLakhan, Abdullah
dc.contributor.authorAbdul Lateef, A.A.
dc.contributor.authorAbd Ghani, Mohd Khanapi
dc.contributor.authorAbdulkareem, Karrar Hameed
dc.contributor.authorMohammed, Mazin Abed
dc.contributor.authorNedoma, Jan
dc.contributor.authorMartinek, Radek
dc.contributor.authorGarcía-Zapirain, Begoña
dc.date.accessioned2026-02-25T12:24:46Z
dc.date.available2026-02-25T12:24:46Z
dc.date.issued2023-10-01
dc.date.updated2026-02-25T12:24:46Z
dc.description.abstractThe Industrial Internet of Healthcare Things (IIoHT) is the emerging paradigm in digital healthcare. Context-aware healthcare sensors, local intelligent watches, healthcare devices, wireless communication technologies, fog, and cloud computing are all parts of the IIoHT used in healthcare. The ubiquitous healthcare services it provides to its users in practice. However, the current IIoHT healthcare frameworks have security and failure issues in mobile fog and cloud networks where they are spread out. This paper presents the secure, fault-tolerant IIoHT Framework based on digital twin (DT) federated learning-enabled fog-cloud models. The DT is an effective technology that makes virtual copies of servers at different locations. DT integrated with federated learning inside the fog and cloud environments, where the failure of tasks and execution improved for healthcare sensor data. The study aims to reduce processing time and the risk of task failure. The study presents the Secure and Fault-Tolerant Strategies (SFTS)-enabled IIoHT framework that optimizes wearable sensor data and executes it with the minimum offloading and processing delays. Simulation results show that the proposed work minimized the security risk by 40%, failure risk of tasks risk by 50%, and the training and testing time by 39% for sensor data during the execution of mobile fog cloud networks.en
dc.description.sponsorshipThis article was co-funded by the European Union under the REFRESH - Research Excellence For REgion Sustainability and High-tech Industries project number CZ.10.03.01/00/22_003/0000048 via the Operational Programme Just Transition. Also, this work was supported by the Ministry of Education, Youth and Sports of the Chezk Republic conducted by VSB - Technical University of Ostrava, Czechia under Grants SP2023/039 and SP2023/042en
dc.identifier.citationLakhan, A., Abdul Lateef, A. A., Abd Ghani, M. K., Abdulkareem, K. H., Mohammed, M. A., Nedoma, J., Martinek, R., & Garcia-Zapirain, B. (2023). Secure-fault-tolerant efficient industrial internet of healthcare things framework based on digital twin federated fog-cloud networks. Journal of King Saud University - Computer and Information Sciences, 35(9). https://doi.org/10.1016/J.JKSUCI.2023.101747
dc.identifier.doi10.1016/J.JKSUCI.2023.101747
dc.identifier.eissn2213-1248
dc.identifier.issn1319-1578
dc.identifier.urihttps://hdl.handle.net/20.500.14454/5241
dc.language.isoeng
dc.publisherKing Saud bin Abdulaziz University
dc.rights© 2023 The Author(s)
dc.subject.otherBlockchain
dc.subject.otherCNN
dc.subject.otherDigital twin
dc.subject.otherFault-tolerant
dc.subject.otherFog-cloud networks
dc.subject.otherIndustry 5.0
dc.subject.otherIoHT
dc.subject.otherSFTS
dc.titleSecure-fault-tolerant efficient industrial internet of healthcare things framework based on digital twin federated fog-cloud networksen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.issue9
oaire.citation.titleJournal of King Saud University - Computer and Information Sciences
oaire.citation.volume35
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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