References of "Boutet, Antoine"
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See detailDyPS: Dynamic, Private and Secure GWAS
Pascoal, Túlio UL; Decouchant, Jérémie UL; Boutet, Antoine et al

in Proceedings on Privacy Enhancing Technologies (2021)

Genome-Wide Association Studies (GWAS) identify the genomic variations that are statistically associated with a particular phenotype (e.g., a disease). The confidence in GWAS results increases with the ... [more ▼]

Genome-Wide Association Studies (GWAS) identify the genomic variations that are statistically associated with a particular phenotype (e.g., a disease). The confidence in GWAS results increases with the number of genomes analyzed, which encourages federated computations where biocenters would periodically share the genomes they have sequenced. However, for economical and legal reasons, this collaboration will only happen if biocenters cannot learn each others’ data. In addition, GWAS releases should not jeopardize the privacy of the individuals whose genomes are used. We introduce DyPS, a novel framework to conduct dynamic privacy-preserving federated GWAS. DyPS leverages a Trusted Execution Environment to secure dynamic GWAS computations. Moreover, DyPS uses a scaling mechanism to speed up the releases of GWAS results according to the evolving number of genomes used in the study, even if individuals retract their participation consent. Lastly, DyPS also tolerates up to all-but-one colluding biocenters without privacy leaks. We implemented and extensively evaluated DyPS through several scenarios involving more than 6 million simulated genomes and up to 35,000 real genomes. Our evaluation shows that DyPS updates test statistics with a reasonable additional request processing delay (11% longer) compared to an approach that would update them with minimal delay but would lead to 8% of the genomes not being protected. In addition, DyPS can result in the same amount of aggregate statistics as a static release (i.e., at the end of the study), but can produce up to 2.6 times more statistics information during earlier dynamic releases. Besides, we show that DyPS can support a larger number of genomes and SNP positions without any significant performance penalty. [less ▲]

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See detailP3LS : Plausible Deniability for Practical Privacy-Preserving Live Streaming
Decouchant, Jérémie UL; Boutet, Antoine; Yu, Jiangshan et al

Scientific Conference (2019, October)

Video consumption is one of the most popular Internet activities worldwide. The emergence of sharing videos directly recorded with smartphones raises important privacy concerns. In this paper we propose ... [more ▼]

Video consumption is one of the most popular Internet activities worldwide. The emergence of sharing videos directly recorded with smartphones raises important privacy concerns. In this paper we propose P3LS , the first practical privacy-preserving peer-to-peer live streaming system. To protect the privacy of its users, P3LS relies on k-anonymity when users subscribe to streams, and on plausible deniability for the dissemination of video streams. Specifically, plausible deniability during the dissemination phase ensures that an adversary is never able to distinguish a user’s stream of interest from the fake streams from a statistical analysis (i.e., using an analysis of variance). We exhaustively evaluate P3LS and show that adversaries are not able to identify the real stream of a user with very high confidence. Moreover, P3LS consumes 30% less bandwidth than the standard k-anonymity approach where nodes fully contribute to the dissemination of k streams. [less ▲]

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