Measuring privacy protection in structured synthetic datasets: A survey

Policymakers are increasingly looking to enhance data mobility, yet safeguard citizens’ privacy. Synthetic data has garnered attention as a privacy enhancing technology. Unfortunately, assessing the degree of privacy protection in synthetic datasets requires insights from several, seemingly disparate fields of expertise. In this chapter, we provide a detailed overview of the relevant legal theory, as well as mathematical, statistical, and computer scientific approaches to privacy assessment in synthetic data. The work contributes to the development of comprehensive and legally sound privacy standards for synthetic data. It will also raise awareness of data privacy and help synthetic data researchers make informed modelling and evaluation decisions.