Evidence map›Paper›PMID 35758787›Full record

ArticleBioinformatics (Oxford, England)2022

Robust fingerprinting of genomic databases.

Tianxi Ji, Erman Ayday, Emre Yilmaz, Pan Li

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Tianxi JiDepartment of Electrical, Computer, and System Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
Erman AydayDepartment of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH 44106, USA.
Emre YilmazDepartment of Computer Science and Engineering Technology, University of Houston-Downtown, Houston, TX 77002, USA.
Pan LiDepartment of Electrical, Computer, and System Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.

Funding

Privacy Challenges of Genomic Data-Sharing Beacons and SolutionsR01LM013429 · NLM · CASE WESTERN RESERVE UNIVERSITY · PI AYDAY, ERMAN · 2020 to 2023
$1.2M
National Library of Medicine of the National Institutes of Health R01LM013429NLM NIH HHS R01 LM013429
6 · The paper itself

Abstract

motivationDatabase fingerprinting has been widely used to discourage unauthorized redistribution of data by providing means to identify the source of data leakages. However, there is no fingerprinting scheme aiming at achieving liability guarantees when sharing genomic databases. Thus, we are motivated to fill in this gap by devising a vanilla fingerprinting scheme specifically for genomic databases. Moreover, since malicious genomic database recipients may compromise the embedded fingerprint (distort the steganographic marks, i.e. the embedded fingerprint bit-string) by launching effective correlation attacks, which leverage the intrinsic correlations among genomic data (e.g. Mendel's law and linkage disequilibrium), we also augment the vanilla scheme by developing mitigation techniques to achieve robust fingerprinting of genomic databases against correlation attacks.

resultsVia experiments using a real-world genomic database, we first show that correlation attacks against fingerprinting schemes for genomic databases are very powerful. In particular, the correlation attacks can distort more than half of the fingerprint bits by causing a small utility loss (e.g. database accuracy and consistency of SNP-phenotype associations measured via P-values). Next, we experimentally show that the correlation attacks can be effectively mitigated by our proposed mitigation techniques. We validate that the attacker can hardly compromise a large portion of the fingerprint bits even if it pays a higher cost in terms of degradation of the database utility. For example, with around 24% loss in accuracy and 20% loss in the consistency of SNP-phenotype associations, the attacker can only distort about 30% fingerprint bits, which is insufficient for it to avoid being accused. We also show that the proposed mitigation techniques also preserve the utility of the shared genomic databases, e.g. the mitigation techniques only lead to around 3% loss in accuracy. AVAILABILITY AND IMPLEMENTATION: https://github.com/xiutianxi/robust-genomic-fp-github.

Indexed as

AlgorithmsGenomicsDatabases, Factual

Identifiers

PMID35758787
PMCPMC9236581

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.