Privacy-Preserving Analysis of Distributed Medical Data

Project leader: René Raab
Project members: Björn Eskofier
Start date: 1. July 2023
End date:

Abstract

Recent legislative development, such as the European Health Data Space, expand access to anonymizied health data for various entities. While these advances offer opportunities for medical research and innovation, they also increase the risk of compromising individuals' privacy.

This project addresses the critical tension between the growing utility of health data and the need to protect individual privacy through organizational, infrastructural, and technical approaches. A key component of the technical solutions is privacy-enhancing technologies (PETs), such as secure multi-party computation and (local) differential privacy, which safeguard individuals' privacy while enabling the statistical analysis of aggregate data.

Related Publications

• Raab R., Berrang P., Gerhart P., Schröder D.:
  SoK: Descriptive Statistics Under Local Differential Privacy
  In: Proceedings on Privacy Enhancing Technologies 2025 (2025), p. 118-149
  ISSN: 2299-0984
  DOI: 10.56553/popets-2025-0008
  BibTeX: Download
• Raab R., Küderle A., Zakreuskaya A., Stern AD., Klucken J., Kaissis G., Rueckert D., Boll S., Eils R., Wagener H., Eskofier B.:
  Federated electronic health records for the European Health Data Space
  In: The Lancet Digital Health 5 (2023), p. e840-e847
  ISSN: 2589-7500
  DOI: 10.1016/S2589-7500(23)00156-5
  URL: https://www.thelancet.com/journals/landig/article/PIIS2589-7500(23)00156-5/fulltext
  BibTeX: Download