Privacy and synthetic data

This working package focuses on the new methods of respecting data subject privacy in the use of register data. One such method is differential privacy that aims to provide strong and rigorous privacy guarantees via synthetic data. The working package will develop methods to evaluate the differences between synthetic and original data as well as to estimate their impact on the results of downstream analyses. The working package will also produce new knowledge about user expectations about anonymity and legal requirements for privacy.

Principal investigator

Antti Honkela

The consortium deputy PI

Associate Professor

Data Science

University of Helsinki

antti.honkela@helsinki.fi

Link to the researcher profile

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Related scientific publications

Jälkö, J & Lagerspetz, E & Haukka, J & Tarkoma, S & Honkela, A & Kaski, S (2021) Privacy-preserving data sharing via probabilistic modeling