Research Project
ENCRYPT: a scalable and practical privacy preserving framework
The project allows researchers and developers to process data stored in federated cross-border dataspaces in a GDPR-compliant way.
Where: international
Where: international
Challenge
The deluge of big data, accompanied by developments in software and hardware technologies exploiting them, has created new opportunities for research and industry. Although several technologies have been developed to facilitate the processing of data while preserving privacy, they have not made significant inroads into real use cases.
Approach
ENCRYPT develops a scalable, practical, adaptable privacy preserving framework and at the same time validates it in a comprehensive validation campaign in three sectors, namely the health sector, the cybersecurity sector, and the finance sector including cross-border processing of data.
Digital Ecosystem
Solution
Digital Ecosystem
ENCRYPT develops a recommendation engine for citizens and end-users, providing them with personalised suggestions on privacy. The framework considers the needs and preferences of relevant actors, and is validated in a comprehensive, 3-phase validation campaign, comprising in-lab validation tests, use cases provided by consortium partners and external use cases including privacy preserving computations on federated medical datasets.
Engineering contributes to the definition of the Methodological IoT Trust and Identity Framework ans is involved in the system integration, validation, and evaluation of the solution.
EU co-founding project, contract No. 101070670
Financing Framework
Results
Technologies
AI & Advanced Analytics
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Cybersecurity
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