Addressing Beacon re-identification attacks: quantification and mitigation of privacy risks. (20th February 2017)

• Record Type: Journal Article
• Authors: Raisaro, Jean Louis; Tramèr, Florian; Ji, Zhanglong; Bu, Diyue; Zhao, Yongan; Carey, Knox; Lloyd, David; Sofia, Heidi; Baker, Dixie; Flicek, Paul; Shringarpure, Suyash; Bustamante, Carlos; Wang, Shuang; Jiang, Xiaoqian; Ohno-Machado, Lucila; Tang, Haixu; Wang, XiaoFeng; Hubaux, Jean-Pierre
• Is Part Of: Journal of the American Medical Informatics Association. Volume 24:Number 4(2017:Jul.)
• Page Start: 799
• Page End: 805
• Publication Date: 2017-02-20
• Subjects: genomic privacy -- ga4gh -- beacon -- re-identification -- genomic data sharing; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocw167
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: The Global Alliance for Genomics and Health (GA4GH) created the Beacon Project as a means of testing the willingness of data holders to share genetic data in the simplest technical context—a query for the presence of a specified nucleotide at a given position within a chromosome. Each participating site (or "beacon") is responsible for assuring that genomic data are exposed through the Beacon service only with the permission of the individual to whom the data pertains and in accordance with the GA4GH policy and standards. While recognizing the inference risks associated with large-scale data aggregation, and the fact that some beacons contain sensitive phenotypic associations that increase privacy risk, the GA4GH adjudged the risk of re-identification based on the binary yes/no allele-presence query responses as acceptable. However, recent work demonstrated that, given a beacon with specific characteristics (including relatively small sample size and an adversary who possesses an individual's whole genome sequence), the individual's membership in a beacon can be inferred through repeated queries for variants present in the individual's genome. In this paper, we propose three practical strategies for reducing re-identification risks in beacons. The first two strategies manipulate the beacon such that the presence of rare alleles is obscured; the third strategy budgets the number of accesses per user for each individual genome. Using a beacon containing data from the 1000 Genomes Project, we demonstrate that the proposed strategies can effectively reduce re-identification risk in beacon-like datasets.