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

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.This research was funded by the Qatar National Library, Doha, Qatar and Qatar University internal grant IRCC-2021-010