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FeatureCloud

Financiado

Cerrado

Privacy preserving federated machine learning and blockchaining for reduced cybe...

Privacy preserving federated machine learning and blockchaining for reduced cyber risks in a world of distributed healthcare The digital revolution, in particular big data and artificial intelligence (AI), offer new opportunities to transform healthcare. However, it also harbors risks to the safety of sensitive clinical data stored in critical healthcar... ver más

31/12/2023

UHAM

5M€

Presupuesto del proyecto: 5M€

Líder del proyecto

UNIVERSITY OF HAMBURG No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2023-12-31

SU-TDS-02-2018: Toolkit for assessing and reducing... Specific Challenge:Digital technologies such as Big data, Internet of Things, Robotics, Artificial I...

I+D

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Características del participante

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

10 Participantes

UHAM

734.88K€ | Lider

SBA

500.00K€ | Participante

CONCENTRIS RESEARCH MANAGEME...

355.00K€ | Participante

RESEARCH INSTITUTE AG CO KG

347.37K€ | Participante

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Duración del proyecto: 61 meses Fecha Inicio: 2018-11-07
Fecha Fin: 2023-12-31

Líder del proyecto

UNIVERSITY OF HAMBURG No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 5M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The digital revolution, in particular big data and artificial intelligence (AI), offer new opportunities to transform healthcare. However, it also harbors risks to the safety of sensitive clinical data stored in critical healthcare ICT infrastructure. In particular data exchange over the internet is perceived insurmountable posing a roadblock hampering big data based medical innovations. FeatureCloud’s transformative security-by-design concept will minimize the cyber-crime potential and enable first secure cross-border collaborative data mining endeavors. FeatureCloud will be implemented into a software toolkit for substantially reducing cyber risks to healthcare infrastructure by employing the world-wide first privacy-by-architecture approach, which has two key characteristics: (1) no sensitive data is communicated through any communication channels, and (2) data is not stored in one central point of attack. Federated machine learning (for privacy-preserving data mining) integrated with blockchain technology (for immutability and management of patient rights) will safely apply next-generation AI technology for medical purposes. Importantly, patients will be given effective means of revoking previously given consent at any time. Our ground-breaking new cloud-AI infrastructure only exchanges learned model representations which are anonymous by default. Collectively, our highly interdisciplinary consortium from IT to medicine covers all aspects of the value chain: assessment of cyber risks, legal considerations and international policies, development of federated AI technology coupled to blockchaining, app store and user interface design, implementation as certifiable prognostic medical devices, evaluation and translation into clinical practice, commercial exploitation, as well as dissemination and patient trust maximization. FeatureCloud’s goals are bold, necessary, achievable, and paving the way for a socially agreeable big data era of the Medicine 4.0 age.

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