Ranjeeth Kumar M

An Adaptive Differential Privacy Framework for Secure Cloud Edge Federated Learning using Gradient Norm Dynamics

The concept of Federated Learning (FL) allows training models in a decentralized way without distributing raw data but, nonetheless, the gradients are vulnerable to privacy attacks that include gradient inversion, reconstruction, and membership inference. Differential Privacy (DP) is broadly used to address these risks...