Reviews: Deep Leakage from Gradients

The paper presents an attack against federated learning algorithms and shows that when certain conditions apply, it may be possible to reconstruct the raw data from the gradients. This is an interesting observation. Federated learning, despite not having any formal privacy guarantees, is gaining popularity in corporates that operate on large amounts of data. In some cases, it might be used under the assumption that it provides privacy. Therefore, showing that this feeling is wrong may have real world impact.