A Privacy-Preserving and Fault-Tolerant Framework for Real-Time IoMT Analytics via SMPC and Encrypted Graph Neural Networks
The Internet of Medical Things (IoMT) enables continuous health monitoring through distributed wearable and implantable devices but faces critical challenges in privacy, latency, trust, and reliability, particularly when aggregating sensitive physiological data across untrusted networks. In this paper, we propose Graph...