Model Inversion Attack Against Federated Unlearning

Researchers discovered a new attack called federated unlearning inversion attack (FUIA) that can extract private data from federated unlearning (FU, a process designed to remove a specific person's data influence from shared machine learning models across multiple computers). The attack works by having a malicious server observe the model's parameter changes during the unlearning process and reconstruct the forgotten data, undermining the privacy protection that FU is supposed to provide.