IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i5p1197-d1083958.html
   My bibliography  Save this article

A Features-Based Privacy Preserving Assessment Model for Authentication of Internet of Medical Things (IoMT) Devices in Healthcare

Author

Listed:
  • Habib Ullah Khan

    (Department of Accounting and Information Systems, College of Business and Economics, Qatar University, Doha 2713, Qatar)

  • Yasir Ali

    (Higher Education Department Khyber Pakhtunkhwa, Shahzeb Shaheed Government Degree College, Swabi 23430, Pakistan)

  • Faheem Khan

    (Department of Computer Engineering, Gachon University, Seongnam-si 13120, Republic of Korea)

Abstract

Internet of Things (IoT) devices have drawn significant attention over the last few years due to their significant contribution to every domain of life, but the major application of these devices has been witnessed in the healthcare sector. IoT devices have changed the complexion of healthcare set-up, however, the major limitation of such devices is susceptibility to many cyberattacks due to the use of embedded operating systems, the nature of communication, insufficient software updates, and the nature of backend resources. Similarly, they transfer a huge amount of sensitive data via sensors and actuators. Therefore, the security of Internet of Health Things (IoHT) devices remains a prime concern as these devices are prone to various cyberattacks, which can lead to compromising and violating the security of IoT devices. Therefore, IoT devices need to be authenticated before they join the network or communicate within a network, and the applied method of authentication must be robust and reliable. This authentication method has to be evaluated before being implemented for the authentication of IoT devices/equipment in a healthcare environment. In this study, an evaluation framework is introduced to provide a reliable and secure authentication mechanism based on authentication features. The proposed framework evaluates and selects the most appropriate authentication scheme/method based on evaluating authentication features using a hybrid multicriteria decision-making approach. It completes this in two steps: in the first step, the analytic hierarchy process (AHP) method is applied for assigning criteria weights; and in the second step, the technique for order preference by similarity to ideal solution (TOPSIS) approach selects the best authentication solution for IoHT devices based upon identified authentication features. This is the first attempt to present a features-based authentication model for selecting the improved authentication solution employed in IoHT devices.

Suggested Citation

  • Habib Ullah Khan & Yasir Ali & Faheem Khan, 2023. "A Features-Based Privacy Preserving Assessment Model for Authentication of Internet of Medical Things (IoMT) Devices in Healthcare," Mathematics, MDPI, vol. 11(5), pages 1-17, February.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:5:p:1197-:d:1083958
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/5/1197/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/5/1197/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Muhammad Tahir & Muhammad Sardaraz & Shakoor Muhammad & Muhammad Saud Khan, 2020. "A Lightweight Authentication and Authorization Framework for Blockchain-Enabled IoT Network in Health-Informatics," Sustainability, MDPI, vol. 12(17), pages 1-23, August.
    Full references (including those not matched with items on IDEAS)

    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. Raman Singh & Sean Sturley & Hitesh Tewari, 2023. "Blockchain-Enabled Chebyshev Polynomial-Based Group Authentication for Secure Communication in an Internet of Things Network," Future Internet, MDPI, vol. 15(3), pages 1-15, February.
    2. Kithmini Godewatte Arachchige & Philip Branch & Jason But, 2023. "Evaluation of Blockchain Networks’ Scalability Limitations in Low-Powered Internet of Things (IoT) Sensor Networks," Future Internet, MDPI, vol. 15(9), pages 1-23, September.

    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:jmathe:v:11:y:2023:i:5:p:1197-:d:1083958. 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.