Introduction:    Federated learning (FL) is a machine learning technique used to train a shared model on multiple devices without exchanging their data. Instead, each device trains the model on its local data and shares only any updates to model parameters with the central server; then this central server aggregates updates from all devices and develops a global model before sending...