LAPSE:2023.19791
Published Article
LAPSE:2023.19791
IoT Solution for AI-Enabled PRIVACY-PREServing with Big Data Transferring: An Application for Healthcare Using Blockchain
Mohamed Elhoseny, Khalid Haseeb, Asghar Ali Shah, Irshad Ahmad, Zahoor Jan, Mohammed. I. Alghamdi
March 9, 2023
Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable services in emerging fields. An IoT-based healthcare solution facilitates patients, hospitals, and professionals to observe real-time and critical data. In the literature, most of the solution suffers from data intermission, high ethical standards, and trustworthiness communication. Moreover, network interruption with recurrent expose of sensitive and personal health data decreases the reliance on network systems. Therefore, this paper intends to propose an IoT solution for AI-enabled privacy-preserving with big data transferring using blockchain. Firstly, the proposed algorithm uses a graph-modeling to develop a scalable and reliable system for gathering and transmitting data. In addition, it extracts the subset of nodes using the artificial intelligence approach and achieves efficient services for the healthcare system. Secondly, symmetric-based digital certificates are utilized to offer authentic and confidential transmission with communication resources using blockchain. The proposed algorithm is explored with existing solutions through multiple simulations and proved improvement in terms of realistic parameters.
Keywords
Big Data, constraint network, embedded applications, insecure channels, Internet of things
Suggested Citation
Elhoseny M, Haseeb K, Shah AA, Ahmad I, Jan Z, Alghamdi MI. IoT Solution for AI-Enabled PRIVACY-PREServing with Big Data Transferring: An Application for Healthcare Using Blockchain. (2023). LAPSE:2023.19791
Author Affiliations
Elhoseny M: Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt; Computer Information Technology and the Manager of the Research Support Department, American University in the Emirates, Dubai 503000, United Arab Emirates [ORCID]
Haseeb K: Department of Computer Science, Islamia College Peshawar, Peshawar 25120, Pakistan [ORCID]
Shah AA: Department of Computer Science, Bahria University Lahore Campus, Lahore 54600, Pakistan
Ahmad I: Department of Computer Science, Islamia College Peshawar, Peshawar 25120, Pakistan
Jan Z: Department of Computer Science, Islamia College Peshawar, Peshawar 25120, Pakistan
Alghamdi MI: Department of Computer Science, Al-Baha University, Al Bahah 1988, Saudi Arabia [ORCID]
Journal Name
Energies
Volume
14
Issue
17
First Page
5364
Year
2021
Publication Date
2021-08-28
Published Version
ISSN
1996-1073
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Original Submission
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PII: en14175364, Publication Type: Journal Article
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LAPSE:2023.19791
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doi:10.3390/en14175364
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