Secure and distributed assessment of privacy-preserving GWAS releases

Pascoal, Túlio; Decouchant, Jérémie; Völp, Marcus

doi:10.1145/3528535.3565253

Cited by 2 publications

(1 citation statement)

References 46 publications

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“…For this purpose, one can use the hypothesis test with T r [82] or Λ [88] metrics. Recently, GenDPR [65] proposes a distributed implementation of the LR-test that only manipulates intermediary results in a TEE and does not require genomic data to be exchanged.…”

Section: Related Workmentioning

confidence: 99%

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

Pascoal

Decouchant

Boutet

et al. 2023

PoPETs

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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.

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Section: Related Workmentioning

confidence: 99%

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

Pascoal

Decouchant

Boutet

et al. 2023

PoPETs

View full text Add to dashboard Cite

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Protecting Privacy in Digital Records: The Potential of Privacy-Enhancing Technologies

Lemieux,

Werner

2023

J. Comput. Cult. Herit.

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With increased concerns about data protection and privacy over the past several years, and concomitant introduction of regulations restricting access to personally information (PI), archivists in many jurisdictions now must undertake ‘sensitivity reviews’ of archival documents to determine if they can make those documents accessible to researchers. Such reviews are onerous, given increasing volume of records, and complex, due to how difficult it can be for archivists to identify whether records contain personal information (PI) under the provisions of various laws. Despite research into the application of tools and techniques to automate sensitivity reviews, effective solutions remain elusive. Not yet explored as a solution to the challenge of enabling access to archival holdings subject to privacy restrictions is the application of privacy enhancing technologies (PETs) - a class of emerging technologies that rest on the assumption that a body of documents is confidential or private and must remain so. While seemingly being counter-intuitive to apply PETs to making archives more accessible, we argue that PETs could provide an opportunity to protect PI in archival holdings whilst still enabling research on those holdings. In this paper, to lay a foundation for archival experimentation with use of PETs, we contribute an overview of these technologies based on a scoping review and discuss possible use cases and future research directions.

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Secure and distributed assessment of privacy-preserving GWAS releases

Cited by 2 publications

References 46 publications

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

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

Protecting Privacy in Digital Records: The Potential of Privacy-Enhancing Technologies

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