ENCRYPT will develop a scalable, practical, adaptable privacy preserving framework, allowing researchers and developers to process data stored in federated cross-border data spaces in a GDPR compliant way. Within this framework, a recommendation engine for citizens and end-users will be developed, providing them with personalised suggestions on privacy preserving technologies depending on the sensitivity of data and the accepted trade-off between the degree of security and the overall system performance.

In ENCRYPT, the School of Informatics contributes to the development of the project’s semantic backbone by designing and implementing the Knowledge Graph infrastructure that enables secure, privacy-preserving integration of heterogeneous data sources across domains such as healthcare, finance, and cybersecurity, ensuring semantic interoperability, alignment with FAIR principles, and support for advanced analytics and cross-sector data sharing.