Practical Feasibility of Gradient Inversion Attacks in Federated Learning

Viktor Valadi, Mattias à kesson, Johan Östman +3

Gradient inversion attacks are often presented as a serious privacy threat in federated learning, with recent work reporting increasingly strong reconstructions under favorable exp…