Raisaro, Jean LouisTroncoso-Pastoriza, Juan RamonEl-Zein, YamaneHumbert, MathiasTroncoso, CarmelaFellay, JacquesHubaux, Jean-Pierre2021-05-082021-05-082021-05-082020-01-0110.3233/SHTI200158https://infoscience.epfl.ch/handle/20.500.14299/177936WOS:000625278800048One major obstacle to developing precision medicine to its full potential is the privacy concerns related to genomic-data sharing. Even though the academic community has proposed many solutions to protect genomic privacy, these so far have not been adopted in practice, mainly due to their impact on the data utility. We introduce GenoShare, a framework that enables individual citizens to understand and quantify the risks of revealing genome-related privacy-sensitive attributes (e.g., health status, kinship, physical traits) from sharing their genomic data with (potentially untrusted) third parties. GenoShare enables informed decision-making about sharing exact genomic data, by jointly simulating genome-based inference attacks and quantifying the risk stemming from a potential data disclosure.Health Care Sciences & ServicesMedical Informaticsgenomic privacyprivacy-conscious toolsrisk quantificationinferencetext::conference output::conference proceedings::conference paper