Privacy Preserving Federated Learning
Title: Privacy Preserving Federated Learning
DNr: Berzelius-2024-103
Project Type: LiU Berzelius
Principal Investigator: Sargam Gupta <>
Affiliation: Umeå universitet
Duration: 2024-04-01 – 2024-10-01
Classification: 10201


I plan to work on a privacy-preserving framework for the Deep Leakage from Gradients attack which is quite a popular attack in Federated Learning literature. Currently, I am specifically looking at the mitigation for this particular attack on the " DENSE: Data-Free One-Shot Federated Learning" paper. I also plan to experiment more with the federated settings and different privacy models like k-anonymity and differential privacy.