H2020 grant on Privacy-preserving Big Data technologies

Associate professor Claudio Orlandi has been granted 3,5 mil DKK from the EU Framework Programme, Horizon 2020 for a project called SODA (Scalable Oblivious Data Analytics). The project will be in collaboration between Philips Research, Eindhoven University of Technology, AU, Göttingen University and the Alexandra Institute.

2016.09.06 | Marianne Dammand Iversen

More and more data is being generated, and analyzing this data drives knowledge and value creation across society. Unlocking this potential requires sharing of (often personal) data between organizations, but this meets unwillingness from data subjects and data controllers alike. Hence, techniques that protect personal information for data access, processing, and analysis are needed.

The SODA project will enable practical privacy-preserving analytics of information from multiple data assets using multi-party computation (MPC) techniques for which data does not need to be shared, only made available for encrypted processing. The main technological challenge is to make MPC scale to big data, where we expect to achieve substantial performance improvements.

We will combine expertise from the domains of MPC, differential privacy and data analytics into a comprehensive privacy perspective following a use case-driven approach, exploiting Philips leading positions in healthcare applications.
The project will also ensure improved compliance with EU data privacy regulation (by performing legal analysis in a feedback loop with technical development) and making data subjects more confident to enable processing with our techniques (by performing user studies in a feedback loop with our consent control component).

Read the full press release here (in Danish)

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