Two arXiv papers sharpen the synthetic data privacy debate

Two new arXiv papers examine opposite sides of synthetic data privacy. One shows that black-box querying and clustering can reveal membership leakage from generative models, while the other proposes an FHE-based training framework that keeps tabular data encrypted throughout synthetic data generation.