GenoShare: Supporting Privacy-Informed Decisions for Sharing Individual-Level Genetic Data.

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Ressource 1Download: SHTI-270-SHTI200158.pdf (179.32 [Ko])
State: Public
Version: Final published version
License: CC BY-NC 4.0
Serval ID
serval:BIB_E4D4CB80455C
Type
A part of a book
Publication sub-type
Chapter: chapter ou part
Collection
Publications
Institution
Title
GenoShare: Supporting Privacy-Informed Decisions for Sharing Individual-Level Genetic Data.
Title of the book
Digital Personalized Health and Medicine
Author(s)
Raisaro J.L., Troncoso-Pastoriza J.R., El-Zein Y., Humbert M., Troncoso C., Fellay J., Hubaux J.P.
Publisher
IOS Press
ISBN
978-1-64368-082-8
ISSN
1879-8365 (Electronic)
ISSN-L
0926-9630
Publication state
Published
Issued date
16/06/2020
Peer-reviewed
Oui
Volume
270
Series
Studies in health technology and informatics
Pages
238-241
Language
english
Abstract
One 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.
Keywords
Confidentiality, Databases, Genetic/ethics, Disclosure, Genetic Privacy, Genome, Genomics/ethics, Humans, Information Dissemination/ethics, Informed Consent, Medical Record Linkage, genomic privacy, inference, privacy-conscious tools, risk quantification
Pubmed
Web of science
Create date
03/07/2020 19:36
Last modification date
30/08/2024 11:39
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