1. Introducing the TRUMPET project: TRUstworthy Multi-site Privacy Enhancing Technologies
- Author
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Pedrouzo-Ulloa, Alberto, Ramon, Jan, Duflot, Patrick, Pérez-González, Fernando, Lilova, Siyanna, Chihani, Zakaria, Gentili, Nicola, Ulivi, Paola, Hoque, Mohammad Ashadul, Mukammel, Twaha, Pritzker, Zeev, Lemesle, Augustin, Loureiro-Acuña, Jaime, Martı́nez, Xavier, Jiménez-Balsa, Gonzalo, Universidade de Vigo, Machine Learning in Information Networks (MAGNET), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Universitaire de Liège (CHU-Liège), Timelex, Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Technovative Solutions, Arteevo Technologies, Centro Tecnoloxico de Telecomunicacions de Galicia (Gradiant), and European Project: 101070038,TRUMPET
- Subjects
Privacy Metrics ,Patient Data Privacy ,AI ,Federated Learning Privacy Metrics Privacy Enhancing Technologies General Data Protection Regulation Clinical Cancer Research Patient Data Privacy ,Healthcare ,Clinical Cancer Research ,[INFO]Computer Science [cs] ,Privacy Enhancing Technologies ,Federated Learning ,General Data Protection Regulation - Abstract
International audience; This paper is an overview of the EU-funded project TRUMPET (https://trumpetproject.eu/), and gives an outline of its scope and main technical aspects and objectives. In recent years, Federated Learning has emerged as a revolutionary privacy-enhancing technology. However, further research has cast a shadow of doubt on its strength for privacy protection. The goal of TRUMPET is to research and develop novel privacy enhancement methods for Federated Learning, and to deliver a highly scalable Federated AI service platform for researchers, that will enable AI-powered studies of siloed, multi-site, crossdomain, cross-border European datasets with privacy guarantees that follow the requirements of GDPR. The generic TRUMPET platform will be piloted, demonstrated and validated in the specific use case of European cancer hospitals, allowing researchers and policymakers to extract AI-driven insights from previously inaccessible cross-border, cross-organization cancer data, while ensuring the patients' privacy.
- Published
- 2023