Marginals and Malice

Duration: 1 hour 2 mins

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Description:	Dwork, C (Microsoft Research) Wednesday 6th July 2016 -13:30 to 14:30


Created:	2016-07-07 11:14
Collection:	Data Linkage and Anonymisation
Publisher:	Isaac Newton Institute
Copyright:	Dwork, C
Language:	eng (English)
Distribution:	World (downloadable)
Explicit content:	No
Aspect Ratio:	16:9
Screencast:	No
Bumper:	UCS Default
Trailer:	UCS Default


Abstract:	In 2008 Homer et al rocked the genomics community with a discovery that altered the publication policies of the US NIH and the Wellcome Trust, showing that mere allele frequency statistics would permit a forensic analyst -- or a privacy attacker -- to determine the presence of an individual's DNA in a forensic mix -- or a case group. These results were seen as particularly problematic for Genome-Wide Association Studies (GWAS), where the marginals are SNP minor allele frequency statistics (MAFs). In this talk, we review the lessons of Homer et al. and report on recent generalizations and strengthenings of the attack, establishing the impossibility of privately reporting "too many" MAFs with any reasonable notion of accuracy. We then present a differentially private approach to finding significant SNPs that controls the false discovery rate. The apparent contradiction with the impossibility result is resolved by a relaxation of the problem, in which we limit the total number of potentially significant SNPs that are reported. Joint work with Smith, Steinke, Ullman, and Vadhan (lower bounds); and Su and Zhang (FDR control).

Abstract:

In 2008 Homer et al rocked the genomics community with a discovery that altered the publication policies of the US NIH and the Wellcome Trust, showing that mere allele frequency statistics would permit a forensic analyst -- or a privacy attacker -- to determine the presence of an individual's DNA in a forensic mix -- or a case group. These results were seen as particularly problematic for Genome-Wide Association Studies (GWAS), where the marginals are SNP minor allele frequency statistics (MAFs).

In this talk, we review the lessons of Homer et al. and report on recent generalizations and strengthenings of the attack, establishing the impossibility of privately reporting "too many" MAFs with any reasonable notion of accuracy.

We then present a differentially private approach to finding significant SNPs that controls the false discovery rate. The apparent contradiction with the impossibility result is resolved by a relaxation of the problem, in which we limit the total number of potentially significant SNPs that are reported.

Joint work with Smith, Steinke, Ullman, and Vadhan (lower bounds); and Su and Zhang (FDR control).

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Marginals and Malice