@inproceedings{
boudewijn2023privacy,
title={Privacy Measurements in Tabular Synthetic Data: State of the Art and Future Research Directions},
author={Alexander Theodorus Petrus Boudewijn and Andrea Filippo Ferraris and Daniele Panfilo and Vanessa Cocca and Sabrina Zinutti and Karel De Schepper and Carlo Rossi Chauvenet},
booktitle={NeurIPS 2023 Workshop on Synthetic Data Generation with Generative AI},
year={2023},
url={https://openreview.net/forum?id=DO8YT1pt4L}
}
Synthetic data (SD) have garnered attention as a privacy enhancing technology. Unfortunately, there is no standard for assessing their degree of privacy protection. In this paper, we discuss proposed assessment approaches. This contributes to the development of SD privacy standards; stimulates multi-disciplinary discussion; and helps SD researchers make informed modeling and evaluation decisions.
Privacy Measurements in Tabular Synthetic Data: State of the Art and Future Research Directions
Alexander Theodorus Petrus Boudewijn Andrea Filippo Ferraris Daniele Panfilo Vanessa Cocca Sabrina Zinutti Karel De Schepper Carlo Rossi Chauvenet