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dc.contributor.authorLakhan, Abdullah
dc.contributor.authorMohammed, Mazin Abed
dc.contributor.authorAbdulkareem, Karrar Hameed
dc.contributor.authorAbd Ghani, Mohd Khanapi
dc.contributor.authorMarhoon, Haydar Abdulameer
dc.contributor.authorNedoma, Jan
dc.contributor.authorMartinek, Radek
dc.contributor.authorGarcia-Zapirain, Begoña
dc.date.accessioned2024-03-26T09:35:32Z
dc.date.available2024-03-26T09:35:32Z
dc.date.issued2023
dc.identifier.citationInternet of Things. 2023, vol. 24, art. no. 100928.cs
dc.identifier.issn2543-1536
dc.identifier.issn2542-6605
dc.identifier.urihttp://hdl.handle.net/10084/152429
dc.description.abstractIn today’s digital healthcare landscape, numerous clinical institutions collaborate to enhance healthcare quality in a ubiquitous fog and cloud environment. Data fusion plays a vital role in healthcare collaboration, enabling the integration of diverse healthcare sources. The primary advantage is the improvement of healthcare treatments and the availability of services throughout the network. However, despite these benefits, there is room for improvement in addressing various security issues regarding collaboration among clinical healthcare institutions to meet data fusion requirements. The primary challenge lies in processing lung cancer workflow data fusion on heterogeneous nodes while ensuring security in fog cloud networks. As a result, security emerges as a critical issue in the digital healthcare system operating within this ubiquitous environment. We present the secure Blockchain Internet of Medical Things (BIoMT) architecture for lung cancer workflow data fusion processing in fog cloud networks. The BIoMT architecture introduces the Blockchain Data Fusion Secure (BDFS) algorithm framework, which consists of task scheduling and blockchain validation schemes. The study aims to minimize the makespan of the lung workflow tasks based on security and deadline constraints in fog and cloud networks. We consider security at an advanced level, where runtime ransomware attacks are also identified in fog and cloud networks. Simulation results demonstrate that BDFS outperforms all existing BIoMT architectures regarding workflow processing while adhering to the specified constraints. Overall, the BDFS algorithm presented in the BIoMT architecture provides an efficient and secure solution for lung cancer workflow data fusion in fog cloud networks, contributing to the advancement of digital healthcare systems in a ubiquitous environment.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesInternet of Thingscs
dc.relation.urihttps://doi.org/10.1016/j.iot.2023.100928cs
dc.rights© 2023 Elsevier B.V. All rights reserved.cs
dc.subjectBIoMTcs
dc.subjectcancercs
dc.subjectBDFScs
dc.subjectcybersecuritycs
dc.subjectlungcs
dc.subjectfraud-analysiscs
dc.subjectblockchaincs
dc.titleSecure blockchain assisted Internet of Medical Things architecture for data fusion enabled cancer workflowcs
dc.typearticlecs
dc.identifier.doi10.1016/j.iot.2023.100928
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume24cs
dc.description.firstpageart. no. 100928cs
dc.identifier.wos001091486500001


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