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Article

Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

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Artificial Intelligence and Data Analytics (AIDA) Lab, CCIS Prince Sultan University, Riyadh 11586, Saudi Arabia
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Department of Computer Science, Islamia College Peshawar, Peshawar 25000, Pakistan
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Integrated Management Coastal Research Institute, Universitat Politecnica de Valencia, 46730 Valencia, Spain
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School of Computing and Digital Technologies, Staffordshire University, Stoke ST4 2DE, UK
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Author to whom correspondence should be addressed.
Academic Editors: Jaume Segura-Garcia and Santiago Felici-Castell
Energies 2021, 14(19), 6414; https://doi.org/10.3390/en14196414
Received: 21 August 2021 / Revised: 29 September 2021 / Accepted: 4 October 2021 / Published: 7 October 2021
(This article belongs to the Special Issue New Trends on Internet-of-Things (IoT))
Internet of Things (IoT) is a developing technology for supporting heterogeneous physical objects into smart things and improving the individuals living using wireless communication systems. Recently, many smart healthcare systems are based on the Internet of Medical Things (IoMT) to collect and analyze the data for infectious diseases, i.e., body fever, flu, COVID-19, shortness of breath, etc. with the least operation cost. However, the most important research challenges in such applications are storing the medical data on a secured cloud and make the disease diagnosis system more energy efficient. Additionally, the rapid explosion of IoMT technology has involved many cyber-criminals and continuous attempts to compromise medical devices with information loss and generating bogus certificates. Thus, the increase in modern technologies for healthcare applications based on IoMT, securing health data, and offering trusted communication against intruders is gaining much research attention. Therefore, this study aims to propose an energy-efficient IoT e-health model using artificial intelligence with homomorphic secret sharing, which aims to increase the maintainability of disease diagnosis systems and support trustworthy communication with the integration of the medical cloud. The proposed model is analyzed and proved its significance against relevant systems. View Full-Text
Keywords: health system; artificial intelligence; inflectional diseases; energy efficiency; homomorphic secrets health system; artificial intelligence; inflectional diseases; energy efficiency; homomorphic secrets
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MDPI and ACS Style

Rehman, A.; Saba, T.; Haseeb, K.; Larabi Marie-Sainte, S.; Lloret, J. Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing. Energies 2021, 14, 6414. https://doi.org/10.3390/en14196414

AMA Style

Rehman A, Saba T, Haseeb K, Larabi Marie-Sainte S, Lloret J. Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing. Energies. 2021; 14(19):6414. https://doi.org/10.3390/en14196414

Chicago/Turabian Style

Rehman, Amjad, Tanzila Saba, Khalid Haseeb, Souad Larabi Marie-Sainte, and Jaime Lloret. 2021. "Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing" Energies 14, no. 19: 6414. https://doi.org/10.3390/en14196414

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