ArticleJournal of the American Medical Informatics Association : JAMIA
An evaluation of the current state of genomic data privacy protection technology and a roadmap for the future.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
39 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Privacy technology to support data sharing for comparative effectiveness research: a systematic review.Medical care · 2013Pooled it
- Sociotechnical safeguards for genomic data privacy.Nature reviews. Genetics · 2022Review
- Identifying individuals using proteomics: are we there yet?Frontiers in molecular biosciences · 2022Review
- A Sequence Obfuscation Method for Protecting Personal Genomic Privacy.Frontiers in genetics · 2022Article
- Using game theory to thwart multistage privacy intrusions when sharing data.Science advances · 2021Article
- Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics.Nature communications · 2021Article
- Responsible, practical genomic data sharing that accelerates research.Nature reviews. Genetics · 2020Review
- Privacy challenges and research opportunities for genomic data sharing.Nature genetics · 2020Review
- Patient Dossier: Healthcare queries over distributed resources.PLoS computational biology · 2019Article
- BLOOM: BLoom filter based oblivious outsourced matchings.BMC medical genomics · 2017Article
- A generic solution for web-based management of pseudonymized data.BMC medical informatics and decision making · 2015Article
- Privacy in the Genomic Era.ACM computing surveys · 2015Article
- Genetic data sharing and privacy.Neuroinformatics · 2015Article
- Differentially private genome data dissemination through top-down specialization.BMC medical informatics and decision making · 2014Article
- Ethical and legal implications of whole genome and whole exome sequencing in African populations.BMC medical ethics · 2013Article
- SHARE: system design and case studies for statistical health information release.Journal of the American Medical Informatics Association : JAMIA · 2013Article
- Reducing patient re-identification risk for laboratory results within research datasets.Journal of the American Medical Informatics Association : JAMIA · 2013Article
- Secure management of biomedical data with cryptographic hardware.IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society · 2012Article
- The false security of blind dates: chrononymization's lack of impact on data privacy of laboratory data.Applied clinical informatics · 2012Article
- Identifiability in biobanks: models, measures, and mitigation strategies.Human genetics · 2011Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The incorporation of genomic data into personal medical records poses many challenges to patient privacy. In response, various systems for preserving patient privacy in shared genomic data have been developed and deployed. Although these systems de-identify the data by removing explicit identifiers (e.g., name, address, or Social Security number) and incorporate sound security design principles, they suffer from a lack of formal modeling of inferences learnable from shared data. This report evaluates the extent to which current protection systems are capable of withstanding a range of re-identification methods, including genotype-phenotype inferences, location-visit patterns, family structures, and dictionary attacks. For a comparative re-identification analysis, the systems are mapped to a common formalism. Although there is variation in susceptibility, each system is deficient in its protection capacity. The author discovers patterns of protection failure and discusses several of the reasons why these systems are susceptible. The analyses and discussion within provide guideposts for the development of next-generation protection methods amenable to formal proofs.
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Registered trials
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.