Enabling Analytics on Sensitive Medical Data with Secure Multi-Party Computation
Veeningen, M.; Chatterjea, S.; Horváth, A.Z.óf.; Spindler, G.; Boersma, E.; van der Spek, P.; van der Galiën, O.; Gutteling, J.; Kraaij, W.; Veugen, T.
Studies in Health Technology and Informatics 247: 76-80
2018
ISSN/ISBN: 1879-8365 PMID: 29677926 Document Number: 697666
While there is a clear need to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multi-party computation can enable such data analytics by performing analytics without the need to share the underlying data. We discuss the issue of compliance to European privacy legislation; report on three pilots bringing these techniques closer to practice; and discuss the main challenges ahead to make fully privacy-preserving data analytics in the medical sector commonplace.