New white paper on privacy risks, metrics, and governance in synthetic data
As part of an IEEE Industry Connection on Synthetic Data our colleague Rudolf Mayer, senior researcher at SBA Research, co-authored a white paper on privacy risks, metrics, and governance in synthetic data.
© Niklas Schnaubelt
As (structured) synthetic data is a maturing technology for privacy preservation that facilitates compliance with data protection regulations, it is still difficult to assess when such data can be considered anonymous under existing legal frameworks.
The white paper Toward Practical Anonymity: A White Paper on Privacy Risk, Metrics, and Governance in Synthetic Data provides a comprehensive analysis of the relevant legal and regulatory context, empirical methods for privacy risk evaluation, and adversarial threat modeling approaches; it examines privacy risk metrics and technical mitigation techniques, and governance considerations for enterprise data management and compliance. Finally, the need for industry standard-setting initiatives is underscored, and a recommendation is made to pursue formal standards for privacy-preserving data synthesis.
Authors: A. Boudewijn, M. Coyle, A. Ebert, A. Elbi, M. Elliot, M. Giomi, F. Haddad, S. Kroes, Lamberti A., S. Mangiante, R. Mayer, G. Nye, and M. Slokom