Toward Secure and Anonymous Patient Monitoring: An Authenticated Key Agreement Protocol With Secure De-Anonymization

Smart homes equipped with Internet of Things (IoT)–based remote patient monitoring (RPM) systems significantly improve healthcare delivery for vulnerable populations. However, the transmission of sensitive health data over public networks presents critical privacy and security challenges. Existing authenticated key agreement (AKA) protocols often fall short. They either rely on trusted third parties or lack support for secure patient re-identification. This paper proposes a novel lightweight AKA protocol based on zero-trust security principles. It integrates hash functions and exclusive OR (XOR) operations to ensure mutual authentication, session key (SK) confidentiality, and computational efficiency. The protocol’s security was verified through formal analysis using the ProVerif tool, demonstrating correctness of authentication and session key secrecy. The informal analysis confirmed the resilience to impersonation, replay, man-in-the-middle (MITM), session key, and ephemeral secret leakage (ESL) attacks. A prototype implementation using Python validated the practicality of the reversible anonymization mechanism. Performance analysis showed that the protocol achieved a computational cost of 3.9 milliseconds (ms), a communication cost of 2112 bits, and a storage overhead of 2528 bits. These features make it well-suited for real-timeRPMon resource-limited medical IoT devices. Compared to existing lightweight protocols, the proposed protocol offers both stronger security guarantees and more efficient performance metrics. These results demonstrate that the proposed protocol is a secure, efficient, and privacy-aware solution to safeguard patient data in RPMs.