Inken Hagestedt, Yang Zhang, Mathias Humbert, Pascal Berrang, Haixu Tang, Xiaofeng Wang, M. Backes
{"title":"MBeacon: Privacy-Preserving Beacons for DNA Methylation Data","authors":"Inken Hagestedt, Yang Zhang, Mathias Humbert, Pascal Berrang, Haixu Tang, Xiaofeng Wang, M. Backes","doi":"10.14722/ndss.2019.23064","DOIUrl":null,"url":null,"abstract":"The advancement of molecular profiling techniques \nfuels biomedical research with a deluge of data. To facilitate \ndata sharing, the Global Alliance for Genomics and Health \nestablished the Beacon system, a search engine designed to help \nresearchers find datasets of interest. While the current Beacon \nsystem only supports genomic data, other types of biomedical \ndata, such as DNA methylation, are also essential for advancing \nour understanding in the field. In this paper, we propose the first \nBeacon system for DNA methylation data sharing: MBeacon. As \nthe current genomic Beacon is vulnerable to privacy attacks, such \nas membership inference, and DNA methylation data is highly \nsensitive, we take a privacy-by-design approach to construct \nMBeacon. \nFirst, we demonstrate the privacy threat, by proposing a \nmembership inference attack tailored specifically to unprotected \nmethylation Beacons. Our experimental results show that 100 \nqueries are sufficient to achieve a successful attack with AUC \n(area under the ROC curve) above 0.9. To remedy this situation, \nwe propose a novel differential privacy mechanism, namely SVT2 \n, \nwhich is the core component of MBeacon. Extensive experiments \nover multiple datasets show that SVT2 \ncan successfully mitigate \nmembership privacy risks without significantly harming utility. \nWe further implement a fully functional prototype of MBeacon \nwhich we make available to the research community","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":"21 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2019 Network and Distributed System Security Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14722/ndss.2019.23064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 38
Abstract
The advancement of molecular profiling techniques
fuels biomedical research with a deluge of data. To facilitate
data sharing, the Global Alliance for Genomics and Health
established the Beacon system, a search engine designed to help
researchers find datasets of interest. While the current Beacon
system only supports genomic data, other types of biomedical
data, such as DNA methylation, are also essential for advancing
our understanding in the field. In this paper, we propose the first
Beacon system for DNA methylation data sharing: MBeacon. As
the current genomic Beacon is vulnerable to privacy attacks, such
as membership inference, and DNA methylation data is highly
sensitive, we take a privacy-by-design approach to construct
MBeacon.
First, we demonstrate the privacy threat, by proposing a
membership inference attack tailored specifically to unprotected
methylation Beacons. Our experimental results show that 100
queries are sufficient to achieve a successful attack with AUC
(area under the ROC curve) above 0.9. To remedy this situation,
we propose a novel differential privacy mechanism, namely SVT2
,
which is the core component of MBeacon. Extensive experiments
over multiple datasets show that SVT2
can successfully mitigate
membership privacy risks without significantly harming utility.
We further implement a fully functional prototype of MBeacon
which we make available to the research community