An Enhanced Secure Framework For Authentication And Post-Quantum Homomorphic Encryption Using A Hybrid ECC Approach For Iot-Based Medical Sensor Data

Abstract

The growing deployment of Internet of Things (IoT) technologies in healthcare applications has made it possible to perform a continuous surveillance on patients by using wearable medical sensors, while co-increasing concerns about secure authentication and data confidentiality, as well as long-term cryptographic resistance in the cloud-assisted scenario. The main contribution of this study is to fill the limitations of prior IoT healthcare security systems, which fails to provide protocol-complete authentication, post-quantum readiness and privacy-preserving data computation by presenting an integrated security architecture which caters for future technologies requirements. To this end, we resort to a holistic strategy which leverages an enhanced authentication model along with post-quantum homomorphic encryption based on hybrid-elliptic curve cryptosystem. The authentication step is re-imagined with a BLAKE3-like hash model (which we emulate using BLAKE2b) and follows up an explicit XORs-based recovery verification, granting protocol-faithful validation rather than mere identical hash comparison. The data-security phase presents a new hybrid key-generation solution that combines ECC with the lattice-based secret component to mimic post-quantum hardening, and an ECC-based additive homomorphic encryption protocol for the secure aggregation of medical sensor data encrypted in-the-cloud without compromising real contents. It has been shown that the proposed post-quantum homomorphic ECC framework not only reduces average times in encryption and decryption as compared to a hinterland ECC scheme, but it also provides better stability property at significant lower system utilization costs such as lightweight authentication overhead for IoT devices. The results suggest that strong authentication, quantum-aware cryptographic security and encrypted-domain computation are all possible simultaneously without incurring additional computational overhead. Thus, the proposed scheme is a scalable, efficient, and future- secure solution for secure IoT based healthcare system with cloud-based medical analytics toward trust and data privacy, therefore promoting the confidence of next-generation digital health infrastructures to support secure cloud based medical analytics.