Publication

Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption

Jean-Pierre Hubaux, Jacques Fellay, Juan Ramón Troncoso-Pastoriza, Jean Louis Raisaro, Joao André Gomes de Sá e Sousa, David Jules Froelicher
2021
Journal Articles

Abstract

Existing approaches to sharing of distributed medical data either provide only limited protection of patients' privacy or sacrifice the accuracy of results. Here, the authors propose a federated analytics system, based on multiparty homomorphic encryption (MHE), to overcome these issues.

Official source

https://infoscience.epfl.ch/entities/publication/9082e87e-c9c5-48f3-85af-32af5a1f21bf

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.