A Practical and Scalable Privacy-preserving Framework

Nikos Avgerinos, Salvatore D'Antonio, Irene Kamara, Christos Kotselidis, Ioannis Lazarou, Teresa Mannarino, Georgios Meditskos, Konstantina Papachristopoulou, Angelos Papoutsis, Paolo Roccetti, Martin Zuber, “A Practical and Scalable Privacy-preserving Framework”, IEEE International Conference on Cyber Security and Resilience (CSR), Venice, Italy, 2023, pp. 598-603

Nikos Avgerinos, Salvatore D'Antonio, Irene Kamara, Christos Kotselidis, Ioannis Lazarou, Teresa Mannarino, Georgios Meditskos, Konstantina Papachristopoulou, Angelos Papoutsis, Paolo Roccetti, Martin Zuber

ENCRYPT is an EU funded research initiative, working towards the development of 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. ENCRYPT proposes an intelligent and user-centric platform for the confidential processing of privacy-sensitive data via configurable, optimizable, and verifiable privacy-preserving techniques. Research and development activities leverage, improve, and complement technologies and cryptographic schemes that represent the current state-of-the-art in the field of data-in-use protection. Hence, ENCRYPT builds on top of cutting-edge technologies such as Fully Homomorphic Encryption, Secure Multi-Party Computation, Differential Privacy, Trusted Execution Environment, GPU acceleration, knowledge graphs, and AI-based recommendation systems, making them configurable in terms of security and, most importantly, performance. The ENCRYPT framework is being designed taking into consideration the needs and preferences of relevant actors and will be validated in realistic use cases provided by consortium partners in three sectors, namely healthcare (oncology domain), fintech, and cyber threat intelligence domain. This position paper provides an overview of ENCRYPT by presenting project objectives, use cases, and technology pillars.