Êtes-vous un étudiant de l'EPFL à la recherche d'un projet de semestre?
Travaillez avec nous sur des projets en science des données et en visualisation, et déployez votre projet sous forme d'application sur Graph Search.
The academic community has proposed many solutions to address the privacy concerns associated with genomic-data sharing. However, practitioners have not adopted these solutions due to their impact on the data utility. To address this problem, we introduce GenoShare, a framework that helps practitioners to make informed decisions about the sharing of exact genomic data by providing means to systematically reason about the risk of disclosing privacy-sensitive attributes (e.g., health status, kinship, physical traits). We instantiate GenoShare with three of the most important genomics-oriented inference attacks, and demonstrate its capability to detect potential leakage of sensitive attributes using real data from the 1000 Genomes Project.
Stewart Cole, Andrej Benjak, Charlotte Avanzi, Philippe Busso, Pushpendra Singh, Thyago Leal Calvo