Project description
A healthy dose of big data processing
Big data is data that contains huge and hard-to-manage volumes of structured and unstructured data. It is so big that it is difficult or impossible to process using traditional methods. The EU-funded SECURED project will increase efficiency by scaling up multi-party computation, data anonymisation and synthetic data generation. Focusing on private and unbiased AI and data analytics, it will demonstrate technologies developed in health-related use cases like real-time tumour classification, telemonitoring for children and access to genomic data. In addition to speeding up and facilitating privacy preserving data-driven tools and services for well-being, prevention, diagnosis, treatment and follow-up care, SECURED will also analyse the current ethical and legal challenges to data sharing.
Objective
The overall goal 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 improvements and implementation efficiency (HW and SW), as well as the generalization of primitives and definitions, with the aim of speeding up and facilitating privacy preserving data-driven tools and services for wellbeing, prevention, diagnosis, treatment and follow-up care. SECURED will also analyse the current ethical and legal challenges to data sharing, and is targeted at overcoming current limited adoption of advanced multi-party computation and data anonymization technologies by providing direct support to health technology SMEs through a funding call. To ensure relevance to real-world settings, SECURED will showcase the technologies developed in four health-related use cases provided by partner hospitals and health stakeholders, namely: real-time tumor classification; telemonitoring for children; synthetic data generation for education; access to genomic data.
Fields of science
Programme(s)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
1012WX Amsterdam
Netherlands
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Participants (17)
3015 GD Rotterdam
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1111 Budapest
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28037 Madrid
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
28760 Tres Cantos Madrid
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3001 Leuven
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92230 Gennevilliers
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08034 Barcelona
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28009 Madrid
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3000 Leuven
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106 82 ATHINA
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151 25 Maroussi
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T12 YN60 Cork
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07100 Sassari
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1085 Budapest
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08916 Badalona
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1040 Nicosia
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1040 Bruxelles / Brussel
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