@Article{cmc.2026.077157,
AUTHOR = {Fahad Algarni, Saeed Ullah Jan},
TITLE = {A Verifiably Secure and Efficient Authentication Protocol for Resource-Constrained IoT Devices in Cloud-Assisted E-Healthcare},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/cmc/online/detail/26654},
ISSN = {1546-2226},
ABSTRACT = {With the increasing connectivity and intelligence of Internet-of-Things (IoT) devices, which interface with numerous aspects of our daily lives, security remains a major concern for IoT devices deployed in e-healthcare systems. The existing solutions demonstrate that authentication of IoT devices across all domains, especially in healthcare, poses significant vulnerabilities, including side-channel, insider, and replay attacks. Alternatively, it is not feasible for resource-constrained IoT devices due to the computational, communicational, and space overheads of modular exponentiation or bilinear pairing, or because it requires four to five round-trips for authentication. The rapid growth of IoT in the e-healthcare sector is expected to cross “50 billion” or more by 2030, highlighting desynchronization, man-in-the-middle (MITM) attacks, and unavailability flaws in e-healthcare. If the aforementioned security concerns are not adequately addressed, they will, in turn, escalate and lead to severe consequences. Therefore, this article introduces a security protocol for an e-healthcare system to ensure secure communication for the voluminous data collected by IoT devices and to transfer it to the cloud safely. The proof of correctness and robustness of the proposed protocol was conducted using BAN (Burrows-Abadi-Needham) logic, the Real-Or-Random (ROR) model, the ProVerif verification toolkit, and pragmatic discussions. The performance analysis section was addressed by measuring several key metrics, including communication, computation, space, and energy consumption, along with scalability. The results obtained demonstrate that the communication cost may be reduced by up to 76%, the computation cost by up to 92%, and the energy consumption by up to 31%.},
DOI = {10.32604/cmc.2026.077157}
}