Portal with a set of tools and services to ease the secure sharing of sensitive data
Secure computing platform providing a trusted execution environment
S3 storage management system for sharing the storage between teams
Dedicated services catalogs, such as epidemiology, text anonymization or epidemiology
Specific anonymization and differential privacy tools can be used interactively

EOSC-SIESTA bridges the gap between open science and data protection by applying FAIR principles to sensitive data. Through trusted cloud environments, the project demonstrates that data can be secure, confidential, and controlled while remaining findable, accessible, interoperable, and reusable for scientific research. Read more..

A new EOSC-SIESTA publication by IFCA-CSIC, INRIA, and TU Delft explores privacy protection in Federated Learning using sensitive medical imaging data. The study proposes a metric-privacy-inspired noise calibration strategy that improves global model accuracy while defending against Client Inference Attacks. Read more..

Open Science promotes a transparent and collaborative research ecosystem, driven by Europe’s EOSC initiative. However, sharing sensitive data requires balancing openness with privacy. EOSC-SIESTA addresses this challenge by developing trusted, cloud-based environments and privacy-preserving tools that make sensitive data securely shareable and usable under FAIR principles. Read more..