ArticleBMC medical informatics and decision making2015
FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption.
Article in BMC medical informatics and decision making, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- PRISM: privacy-preserving rare disease analysis using fully homomorphic encryption.Bioinformatics (Oxford, England) · 2025Article
- Heterogeneous bioinformatic data encryption on portable devices.Scientific reports · 2025Article
- Privacy-Enhancing Technologies in Biomedical Data Science.Annual review of biomedical data science · 2024Review
- Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision.Briefings in bioinformatics · 2024Review
- The evolving privacy and security concerns for genomic data analysis and sharing as observed from the iDASH competition.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Privacy-Preserving Artificial Intelligence Techniques in Biomedicine.Methods of information in medicine · 2022Article
- Privacy-preserving dataset combination and Lasso regression for healthcare predictions.BMC medical informatics and decision making · 2021Article
- Efficient verification for outsourced genome-wide association studies.Journal of biomedical informatics · 2021Article
- A secure system for genomics clinical decision support.Journal of biomedical informatics · 2020Article
- Privacy challenges and research opportunities for genomic data sharing.Nature genetics · 2020Review
- Big Data Privacy in Biomedical Research.IEEE transactions on big data · 2020Article
- Privacy-preserving techniques of genomic data-a survey.Briefings in bioinformatics · 2019Review
- A secure SNP panel scheme using homomorphically encrypted K-mers without SNP calling on the user side.BMC genomics · 2019Article
- Towards practical privacy-preserving genome-wide association study.BMC bioinformatics · 2018Article
- Privacy-preserving biomedical data dissemination via a hybrid approach.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Mechanisms to protect the privacy of families when using the transmission disequilibrium test in genome-wide association studies.Bioinformatics (Oxford, England) · 2017Article
- PRESAGE: PRivacy-preserving gEnetic testing via SoftwAre Guard Extension.BMC medical genomics · 2017Article
- BLOOM: BLoom filter based oblivious outsourced matchings.BMC medical genomics · 2017Article
- Security controls in an integrated Biobank to protect privacy in data sharing: rationale and study design.BMC medical informatics and decision making · 2017Article
- A community effort to protect genomic data sharing, collaboration and outsourcing.NPJ genomic medicine · 2017Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundThe increasing availability of genome data motivates massive research studies in personalized treatment and precision medicine. Public cloud services provide a flexible way to mitigate the storage and computation burden in conducting genome-wide association studies (GWAS). However, data privacy has been widely concerned when sharing the sensitive information in a cloud environment.
methodsWe presented a novel framework (FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption) to fully outsource GWAS (i.e., chi-square statistic computation) using homomorphic encryption. The proposed framework enables secure divisions over encrypted data. We introduced two division protocols (i.e., secure errorless division and secure approximation division) with a trade-off between complexity and accuracy in computing chi-square statistics.
resultsThe proposed framework was evaluated for the task of chi-square statistic computation with two case-control datasets from the 2015 iDASH genome privacy protection challenge. Experimental results show that the performance of FORESEE can be significantly improved through algorithmic optimization and parallel computation. Remarkably, the secure approximation division provides significant performance gain, but without missing any significance SNPs in the chi-square association test using the aforementioned datasets.
conclusionsUnlike many existing HME based studies, in which final results need to be computed by the data owner due to the lack of the secure division operation, the proposed FORESEE framework support complete outsourcing to the cloud and output the final encrypted chi-square statistics.
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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.