Secure
Interactive Environments for SensiTive data Analytics

Effective and secure data processing within the European Open Science Cloud

Secure
Interactive Environments for SensiTive data Analytics

Effective and secure data processing within the European Open Science Cloud


Discover our solutions

Interactive dashboard

Portal with a set of tools and services to ease the secure sharing of sensitive data

security hardening

Secure computing platform providing a trusted execution environment

STORAGE

S3 storage management system for sharing the storage between teams

THEMATIC CATALOGS

Dedicated services catalogs, such as epidemiology, text anonymization or epidemiology

PRIVACY TOOLS

Specific anonymization and differential privacy tools can be used interactively



Use cases


Latest from EOSC-SIESTA:

  • Second day of the 2nd EOSC-SIESTA All Hands Meeting

    Second day of the 2nd EOSC-SIESTA All Hands Meeting

    The second day of the 2nd EOSC-SIESTA All Hands Meeting focused on addressing several topics that remained open from the previous day and consolidating the outcomes of the collaborative sessions held during the meeting. The morning began with an update on the integration status of the project’s use cases, where partners shared progress following the… Read more..

  • EOSC-SIESTA holds the first day of its 2nd All Hands Meeting

    EOSC-SIESTA holds the first day of its 2nd All Hands Meeting

    The EOSC-SIESTA consortium met for the first day of the 2nd All Hands Meeting, bringing together project partners to review progress and coordinate the next steps of the project. The meeting began with an overview of the current status of EOSC-SIESTA, including updates on deliverables, milestones and financial aspects. This session helped partners align the… Read more..

  • New service! Train your federated learning models with EOSC SIESTA and AI4EOSC

    New service! Train your federated learning models with EOSC SIESTA and AI4EOSC

    EOSC SIESTA expands its functionalities with a new federated learning (FL) client service, enabling its users to train artificial intelligence models in a distributed, secure, and efficient manner, without the need to directly share data from each client/data owner. Figure 1: Service for creating federated learning clients in the EOSC SIESTA dashboard (left) and the… Read more..


Consortium