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 has developed a text anonymization tool prototype to securely share sensitive cyber incident reports. Created by Universidad de León, the tool uses AI and four anonymization techniques to mask confidential data, enabling safe data reuse for research, machine learning, and collaborative cyber defence. Read more..

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..