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

Descrizione del progetto

Megadati e intelligenza artificiale per innovazioni mediche sicure

I megadati e l’intelligenza artificiale spianano la strada a nuovi percorsi per il miglioramento dell’assistenza sanitaria, ma implicano anche rischi per la sicurezza dei dati clinici sensibili memorizzati nelle infrastrutture TIC sanitarie critiche. Il progetto FeatureCloud, finanziato dall’UE, propone un concetto trasformativo di sicurezza sin dalla progettazione che mira a ridurre la possibilità di reati informatici e a consentire tentativi sicuri di collaborazione transfrontaliera per l’estrazione dei dati. Il concetto sarà applicato a una serie di strumenti software che si avvale del primo metodo di «privacy-by-architecture» a livello mondiale. Le caratteristiche alla base di tale metodo sono l’assenza di condivisione di dati sensibili attraverso qualsiasi canale di comunicazione e la mancata archiviazione dei dati in un punto centrale. FeatureCloud integrerà l’apprendimento automatico federato con la tecnologia blockchain per l’impiego sicuro della tecnologia IA di prossima generazione nelle innovazioni mediche.

Obiettivo

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.

Invito a presentare proposte

H2020-SC1-FA-DTS-2018-2020

Vedi altri progetti per questo bando

Bando secondario

H2020-SC1-FA-DTS-2018-1

Meccanismo di finanziamento

RIA - Research and Innovation action

Coordinatore

UNIVERSITY OF HAMBURG
Contribution nette de l'UE
€ 734 876,39
Indirizzo
MITTELWEG 177
20148 Hamburg
Germania

Mostra sulla mappa

Regione
Hamburg Hamburg Hamburg
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Costo totale
€ 734 876,39

Partecipanti (9)