A scalable and practical privacy-preserving framework
The deluge of big data, accompanied by developments in software and hardware technologies leveraging them, has created new opportunities for research and industry. The main challenges, though, faced by researchers and service providers working with personal data, are stemming from the fact that these data need to be processed in a privacy-preserving way, as they contain sensitive information.
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, due to several reasons. 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.
The ENCRYPT framework will be designed taking into consideration the needs and preferences of relevant actors, and will be validated in a comprehensive, 3-phase validation campaign, comprising i) in-lab validation tests, ii) use cases provided by consortium partners in three sectors, namely the health sector, the cybersecurity sector, and the finance sector, that include cross-border processing of data, and iii) external use cases including privacy preserving computations on federated medical datasets.
ENCRYPT is been realised by a multidisciplinary consortium of 14 partners, comprising six companies (including three SMEs, one start-up, and two enterprises), and eight research institutes/universities, covering the value chain for privacy-preserving computation technologies.