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Privacy preserving federated machine learning and blockchaining for reduced cyber risks in a world of distributed healthcare

Project description

Big Data and AI for safe medical innovations

Big Data and artificial intelligence (AI) pave the way for new pathways in the improvement of healthcare. But they also hide risks for the security of sensitive clinical data stored in critical healthcare ICT infrastructure. The EU-funded FeatureCloud project proposes a transformative security-by-design concept aiming to reduce the possibility of cybercrime and allow safe cross-border collaborative data mining efforts. The concept will be applied to a software toolkit employing the worldwide first privacy-by-architecture method. Central features of this method are no sharing of sensitive data via any communication channels and no data storage in one central point. FeatureCloud will integrate federated machine learning with blockchain technology to safely apply next-generation AI technology in medical innovations.

Objective

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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Keywords

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Topic(s)

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Funding Scheme

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RIA - Research and Innovation action

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Call for proposal

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(opens in new window) H2020-SC1-FA-DTS-2018-2020

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Coordinator

UNIVERSITY OF HAMBURG
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 734 876,39
Address
MITTELWEG 177
20148 Hamburg
Germany

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Region
Hamburg Hamburg Hamburg
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 734 876,39

Participants (9)

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