Empirical Evaluation of Structured Synthetic Data Privacy Metrics: Novel experimental framework

Computer Science > Cryptography and Security [Submitted on 18 Dec 2025 (v1), last revised 2 Apr 2026 (this version, v2)] Empirical Evaluation of Structured Synthetic Data Privacy Metrics: Novel experimental framework Milton Nicolás Plasencia Palacios, Alexander Boudewijn, Sebastiano Saccani, Andrea Filippo Ferraris, Diana Sofronieva, Giuseppe D'Acquisto, Filiberto Brozzetti, Daniele Panfilo, Luca Bortolussi Synthetic data generation is gaining traction as a privacy enhancing technology (PET). When properly generated, synthetic data preserve the analytic utility of real data while avoiding the retention of information that would allow the identification of specific individuals. However, the concept of data privacy remains elusive, making it challenging for practitioners to evaluate and benchmark the degree of privacy protection offered by synthetic data. In this paper, we propose a framework to empirically assess the efficacy of tabular synthetic data privacy quantification methods through controlled, deliberate risk insertion. To demonstrate this framework, we survey existing approaches to synthetic data privacy quantification and the related legal theory. We then apply the framework to the main privacy quantification methods with no-box threat models on publicly available datasets. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2512.16284 [cs.CR]   (or arXiv:2512.16284v2 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2512.16284 Focus to learn more Submission history From: Milton Nicolás Plasencia Palacios [view email] [v1] Thu, 18 Dec 2025 08:09:28 UTC (2,993 KB) [v2] Thu, 2 Apr 2026 22:27:56 UTC (2,993 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2025-12 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)