2018-08-30 The network for improvement of care for patients with chronic pain has received a European grant to build a digital platform connecting patients and professionals. The PEP-team of Digital Security is part of this consortium and contributes PEP-technology to enable researchers to use data gathered in this digital platform in a privacy friendly and secure way. The entire project will take about 3 years to complete.
2018-02-20 Infographic explaining the PEP implementation for the Personalized Parkinson's Project. Available as PDF.
2017-11-13 First study participant has been included. Registration and pseudonimisation of data during the data-collection phase works as designed.
2017-11-01 Version 1.0, has been partly refactored and extended and placed into production environment.
2017-06-29 Version 1.0, supporting the data- and sample collection phase in Personalised Parkinson's Project (PPP) is finished. Will be used for unit tests in the coming months, in preparation of the actual start of the start of PPP scheduled for september.
2017-05-31 Jean Popma's presentation at the PI-lab about Privacy by Design & PEP.
2017-03-30 Alpha for version 1 has been finished.
2016-10-12 Hans Harmannij, one of our project members, has won the Joop Bautz Information Security Award for his master's thesis about Polymorphic Pseudonymization in Educational Identity Federations.
2016-07-04 Column about the project by Jaap-Henk Hoepman in the Financieel Dagblad. Available as PDF.
2016-05-15 Blog post by Lucien Engelen about the PEP project.
Welcome to the PEP project page. This project is about privacy friendly exchange of medical data for specific medical research purposes. The PEP methodology combines advanced encryption with distributed pseudonymisation, and distribution of trusted data with fine-grained access management. The first pilot project is a research data repository for a large scale Parkinson's Disease research project.
The collection and analysis of medical data on a big data scale is becoming an essential approach to understand complicated diseases. In order to gain new insights it is important that international researchers can cooperate: they will have to access each other's data and contribute to the data sets. In many cases, such medical research involves privacy sensitive data about patients. Patients should be able to count on preservation of their privacy and on secure storage of their data. All this should comply with European privacy regulations, which are the most stringent in the world.
The PEP project builds on the Polymorphic Encryption and Pseudonymisation technique developed by Bart Jacobs and Eric Verheul. This technique stores pseudonymised data in encrypted form. Researchers working on the data can only decrypt the parts of the data for which they have access rights.
Pilot:Personalized Parkinson's Project ("Parkinson op Maat")
The first case study performed with the PEP technique is Parkinson op Maat, a large scale Parkison's Disease research project by the medical centre from Radboud University, together with Verily (see their blog). This case study involves monitoring 650 patients over a period of two years, using amongst others wearable devices. The data collected this way will be shared, in pseudonymised form, with top research institutes over the world.
The PEP project has its own funding from public sources, with a current budget of 1.6M Euro; 760K Euro is funded by the Province of Gelderland, and the remainder by Radboud University. Eventually the software will be made publicly available under an open source license.