I-GWAS: Privacy-Preserving Interdependent Genome-Wide Association Studies Article Swipe
Túlio Pascoal
,
Jérémie Decouchant
,
Antoine Boutet
,
Marcus Völp
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.56553/popets-2023-0026
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.56553/popets-2023-0026
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.
Related Topics
Concepts
Genome-wide association study
Computer science
Inference
Interdependence
Genetic association
Genome
Computational biology
Data mining
Biology
Single-nucleotide polymorphism
Genetics
Artificial intelligence
Gene
Political science
Genotype
Law
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.56553/popets-2023-0026
- https://petsymposium.org/popets/2023/popets-2023-0026.pdf
- OA Status
- hybrid
- Cited By
- 2
- References
- 75
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4296551883
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4296551883Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.56553/popets-2023-0026Digital Object Identifier
- Title
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I-GWAS: Privacy-Preserving Interdependent Genome-Wide Association StudiesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-01Full publication date if available
- Authors
-
Túlio Pascoal, Jérémie Decouchant, Antoine Boutet, Marcus VölpList of authors in order
- Landing page
-
https://doi.org/10.56553/popets-2023-0026Publisher landing page
- PDF URL
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https://petsymposium.org/popets/2023/popets-2023-0026.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
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https://petsymposium.org/popets/2023/popets-2023-0026.pdfDirect OA link when available
- Concepts
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Genome-wide association study, Computer science, Inference, Interdependence, Genetic association, Genome, Computational biology, Data mining, Biology, Single-nucleotide polymorphism, Genetics, Artificial intelligence, Gene, Political science, Genotype, LawTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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75Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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