Federated Learning Security

Daniel and Chris discuss the importance of securing federated learning to protect privacy, emphasizing the use of encryption and differential privacy in aggregating data. They highlight the need for further research in developing secure federated averaging algorithms to prevent data reconstruction and ensure compliance across national boundaries.