Privacy Aware and Privacy Preserving Distributed and Robust Machine Learning for Medical Applications

PAROMA-MED will develop, validate and evaluate a platform - based hybrid-cloud delivery framework for privacy- and security- assured services and applications in federative cross-border environments.

To this purpose, the project will develop new architectures, technologies, tools and services to support:

• automatic attestation of federation partners
• privacy- and security - by-design, integrating standard compliance and performance / QoS requirements into a policy framework
• consumers with their rights for opt-in / opt-out consent, portability and right to be forgotten requests, as well as transparency in access to their private-data.
• federative Identity and Access Management, based on Zero Trust principles, continuous risk assessment and on confidentiality, integrity and authenticity insurance
• privacy-preserving and trusted data - storage and - processing in federative environments
• flexible and secure access over the Internet to private-data and service resources
• AI / ML by-design, integrating platform services to be used by application developers for data-intensive applications
• Zero Touch deployment and automatic life-cycle management of services and applications
• managed Privacy and Security operations for automated policy enforcement and cyberthreat detection and mitigation

Efficiency and scalability will be insured by the implementation of cloud-native solutions, while future adoption and further development is insured by open-source implementations.

The project will validate and evaluate the PAROMA-MED framework by developing of a comprehensive Use Case with real users in the Healthcare sector.

The project will create impact on the application- creation and delivery ecosystem (including standardization and legal stakeholders), on society and environment and manage the impact via dedicated activities and communication channels.