
Data reconstruction attacks can be used to train models effectively with leaked data from federated learning, despite challenges in reconstruction quality and label matching.


coremsg

leak-and-learn-training-models-with-leaked-data-from-federated-learning


Leak and Learn: Training Models with Leaked Data from Federated Learning


title_rewrite


The author explores the impact of real-world data priors on data reconstruction attacks, highlighting a discrepancy between theoretical models and practical outcomes. The study emphasizes the significance of incorporating data priors accurately into privacy guarantees for better alignment with real-world scenarios.


investigating-visual-privacy-auditing-with-diffusion-models


Investigating Visual Privacy Auditing with Diffusion Models
