| Project Detail |
Protecting data privacy in a data driven world
Data-driven and AI technologies offer a promising future for all sectors, enhancing the quality of life for all Europeans. However, data leaks and identity compromises pose significant threats to these technologies and could hinder their widespread adoption due to the risks they present. In this context, the EU-funded TrustED project will develop robust self-sovereign identity management methods, incorporating advanced features and combined privacy-enhancing technologies. These methods will provide data spaces with reliable, scalable, and improved data privacy and security. Additionally, the project will enable two services related to personal data within data spaces that exceed existing privacy requirements.
Data-driven innovation will bring enormous benefits for citizens, affecting all sectors of activity and the daily lives of all Europeans. It will enable, for example, AI-driven services to find causes for diseases or share attributes of individuals’ identity to quickly participate, for instance, in social or education activities across Europe. However, identity compromises, leakages or abuses of this kind of data pose serious threats that may compromise the proliferation of data spaces involving personal data, and reduce the opportunities offered by the data economy.
The goal of the TrustED project is to design and develop a robust self-sovereign identity management method with advanced features as well as a set of combined privacy enhancing technologies (PETs) to enable TWO highly scalable and reliable services on personal data within data spaces with privacy guarantees that exceed the requirements of the GDPR, eIDASv2 and EUDI wallet:
(1) A trustworthy federated learning service combined with several PETs that will allow AI-powered studies of siloed datasets with privacy guarantees.
(2) A scalable and reliable self sovereign identity management service combined with methods for AI-based document validation, multimodal biometrics and ZKP-based selective disclosure techniques, that will enable electronic attestation, revocation of credentials and sharing of specific attributes of identity in a privacy preserving way.
The components will be piloted, demonstrated and validated in a minimum viable data space that follows the implementations and deployments defined under the EDC Framework, which is powered by the specifications of the Gaia-X AISBL Trust Framework and the IDSA Data space protocol.
The consortium is composed of 10 interdisciplinary partners: 2 Research Organizations, 3 SMEs, 2 Large Entities, 2 NGOs and 1 Clinical partner with extensive experience and expertise to guarantee the correct performance of the activities and the achievement of the results. |
