Ghazanfar Latif

RP-IoMT: A Robust and Provable Framework for Federated Learning Privacy-Preserving Intelligence in Healthcare IoMT

RP-IoMT is proposed, a robust and privacy-preserving FL framework that integrates secure multi-party computation (MPC), zero-knowledge proof-based gradient verification, and robust aggregation mechanisms to ensure both the correctness and integrity of model updates while maintaining strong privacy guarantees in adversarial IoMT environments.