<ul><li>Federated Learning (FL) allows collaborative model training while protecting privacy by not exposing raw data.</li><li>Gradient Leakage Attacks (GLAs) exploit gradients shared during training to reconstruct clients' data, raising privacy concerns.</li><li>Recent empirical evidence shows that data can still be effectively reconstructed in realistic FL settings despite previous beliefs.</li><li>A novel technique called FedLeak has been developed to address the vulnerabilities, emphasizing the need for stronger defense methods in FL systems.</li></ul>

Boosting Gradient Leakage Attacks: Data Reconstruction in Realistic FL Settings

Discover more