When Synthetic Data Met Regulation

TL;DR

This paper discusses how synthetic data generated by differentially private models can be both anonymized and compliant with regulations, addressing privacy concerns in data sharing.

Contribution

It demonstrates that differentially private generative models can produce synthetic data that meets privacy and regulatory standards.

Findings

Synthetic data can be sufficiently anonymized.

Differential privacy ensures regulatory compliance.

Synthetic data maintains utility for analysis.

Abstract

In this paper, we argue that synthetic data produced by Differentially Private generative models can be sufficiently anonymized and, therefore, anonymous data and regulatory compliant.