Enabling of privacy-friendly analysis of network data and beyond

Today's big data analysis is characterized not only by the required enormous computing power, but also the broadband network connections between computer and "the cloud".

This network traffic contains a lot of privacy-sensitive information, from the terms used in search engines to personal medical information. Recent research on pseudonymisation has shown great progress thanks to the Polymorphic Encryption and Pseudonymisation (PEP) approach.

Thanks to PEP, data cannot simply be combined in the event of a leak, while legitimate data sharing is possible. In this project, computer scientists from Radboud University and University of Twente are working with SURF to further develop this technique so that large amounts of data can be pseudonymised, shared, and analysed in a privacy-friendly manner at high speed.

The results of this project are technical in nature and can be seen as a building block for the project building block for the last two projects (see below), while the other projects described can provide ethical, legal, and social input for this project in achieving the desired degree of privacy and pseudonymisation.

This call is closed

The projects have been awarded, at the bottom of this page the current projects.


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