SOURCE-LINKED INTELLIGENCE

Scaling Up secure Processing, Anonymization and generation of Health Data for EU cross border collaborative research and Innovation

CORDIS · observation · Publication date unknown

l of the SECURED project is to scale up multiparty computation, data anonymization and synthetic data generation, by increasing efficiency and improving security, with a focus on private and unbiased artificial intelligence and data analytics, health-related data and data hubs, and cross-border cooperation. The project will address the limitations that are currently preventing the widespread use of secure multiparty computation and effective anonymization, namely: the limited practical capabilities of current cryptographic schemes for secure multi-party computation protocols, and their performance; the lack of well understood and standardized data anonymization methods for health data; the absence of dynamic and on demand services for generating synthetic data; the complex and ad-hoc nature of current federation protocols for machine learning and AI-based data analytics; the lack of support for health technology providers to implement privacy enhancing technologies, in particular SMEs. SECURED will tackle these challenges by focusing on scaling up privacy technologies via algorithmic

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recordType

award

status

SIGNED

region

EU

value

6999723.25

unit

EUR