A cloud-assisted anonymous and privacy-preserving authentication scheme for internet of medical things

Abstract

With the rapid advancement of the Internet of Medical Things (IoMT) and the increasing adoption of cloud computing, the storage and processing of medical data have become significantly more efficient. However, in cloud-assisted IoMT environments, data is exposed to risks due to open networks and semi-trusted cloud service providers, potentially compromising sensitive information. Ensuring data security is paramount; yet, existing authentication protocols often exhibit limitations, such as high computational overhead and security vulnerabilities. In this paper, we propose a cloud-assisted authentication scheme designed to ensure secure privacy protection for physiological data within the open network environment of IoMT, while accommodating the resource-constrained nature of sensor nodes. Our innovative remote anonymous authentication scheme leverages Elliptic Curve Cryptography to facilitate secure mutual authentication over insecure channels. During the authentication phase, the cloud server cannot ascertain the user's true identity, allowing patients to access services anonymously. To enhance security, we employ proxy re-encryption techniques, enabling users to decrypt the cloud server's encrypted shared intermediate ciphertexts securely. Comprehensive security and privacy analyses, along with performance evaluations, demonstrate that the proposed scheme offers superior cost-effectiveness, enhanced privacy protection, and improved execution efficiency compared to existing solutions.