IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i19p6414-d651352.html
   My bibliography  Save this article

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

Author

Listed:
  • Amjad Rehman

    (Artificial Intelligence and Data Analytics (AIDA) Lab, CCIS Prince Sultan University, Riyadh 11586, Saudi Arabia)

  • Tanzila Saba

    (Artificial Intelligence and Data Analytics (AIDA) Lab, CCIS Prince Sultan University, Riyadh 11586, Saudi Arabia)

  • Khalid Haseeb

    (Department of Computer Science, Islamia College Peshawar, Peshawar 25000, Pakistan)

  • Souad Larabi Marie-Sainte

    (Artificial Intelligence and Data Analytics (AIDA) Lab, CCIS Prince Sultan University, Riyadh 11586, Saudi Arabia)

  • Jaime Lloret

    (Integrated Management Coastal Research Institute, Universitat Politecnica de Valencia, 46730 Valencia, Spain
    School of Computing and Digital Technologies, Staffordshire University, Stoke ST4 2DE, UK)

Abstract

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.

Suggested Citation

  • Amjad Rehman & Tanzila Saba & Khalid Haseeb & Souad Larabi Marie-Sainte & Jaime Lloret, 2021. "Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing," Energies, MDPI, vol. 14(19), pages 1-15, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6414-:d:651352
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/19/6414/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/19/6414/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Amjad Rehman & Khalid Haseeb & Tanzila Saba & Jaime Lloret & Zara Ahmed, 2021. "Mobility Support 5G Architecture with Real-Time Routing for Sustainable Smart Cities," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Amjad Rehman & Tanzila Saba & Khalid Haseeb & Teg Alam & Jaime Lloret, 2022. "Sustainability Model for the Internet of Health Things (IoHT) Using Reinforcement Learning with Mobile Edge Secured Services," Sustainability, MDPI, vol. 14(19), pages 1-14, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Constantin Aurelian Ionescu & Melinda Timea Fülöp & Dan Ioan Topor & Sorinel Căpușneanu & Teodora Odett Breaz & Sorina Geanina Stănescu & Mihaela Denisa Coman, 2021. "The New Era of Business Digitization through the Implementation of 5G Technology in Romania," Sustainability, MDPI, vol. 13(23), pages 1-23, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6414-:d:651352. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.