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Privacy Measurement in Tabular Synthetic Data: State of the Art and Future Research Directions

2023/11/29 by Alexander Boudewijn, Andrea Filippo Ferraris, Daniele Panfilo +4 · 1 voice
Computer Science · Mathematics · #cs.AI #cs.CR #cs.DB #stat.ML

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Abstract

Synthetic data (SD) have garnered attention as a privacy enhancing technology. Unfortunately, there is no standard for quantifying their degree of privacy protection. In this paper, we discuss proposed quantification approaches. This contributes to the development of SD privacy standards; stimulates multi-disciplinary discussion; and helps SD researchers make informed modeling and evaluation decisions.

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