Accéder directement au contenu Accéder directement à la navigation
Nouvelle interface
Communication dans un congrès

I-GWAS: Privacy-Preserving Interdependent Genome-Wide Association Studies

Abstract : Genome-wide Association Studies (GWASes) identify genomic variations that are statistically associated with a trait, such as a disease, in a group of individuals. Unfortunately, careless sharing of GWAS statistics might give rise to privacy attacks. Several works attempted to reconcile secure processing with privacy-preserving releases of GWASes. However, we highlight that these approaches remain vulnerable if GWASes utilize overlapping sets of individuals and genomic variations. In such conditions, we show that even when relying on state-of-the-art techniques for protecting releases, an adversary could reconstruct the genomic variations of up to 28.6% of participants, and that the released statistics of up to 92.3% of the genomic variations would enable membership inference attacks. We introduce I-GWAS, a novel framework that securely computes and releases the results of multiple possibly interdependent GWASes. I-GWAS continuously releases privacy-preserving and noise-free GWAS results as new genomes become available.
Type de document :
Communication dans un congrès
Liste complète des métadonnées

https://hal.inria.fr/hal-03781755
Contributeur : Antoine Boutet Connectez-vous pour contacter le contributeur
Soumis le : mardi 20 septembre 2022 - 16:05:00
Dernière modification le : mercredi 21 septembre 2022 - 03:56:10

Fichier

main.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-03781755, version 1

Collections

Citation

Túlio Pascoal, Jérémie Decouchant, Antoine Boutet, Marcus Völp. I-GWAS: Privacy-Preserving Interdependent Genome-Wide Association Studies. PETS 2023 - 23rd Privacy Enhancing Technologies Symposium, Jul 2023, Lausanne, Switzerland. ⟨hal-03781755⟩

Partager

Métriques

Consultations de la notice

17

Téléchargements de fichiers

7