2024
Privacy-Enhancing Technologies in Biomedical Data Science
Cho H, Froelicher D, Dokmai N, Nandi A, Sadhuka S, Hong M, Berger B. Privacy-Enhancing Technologies in Biomedical Data Science. Annual Review Of Biomedical Data Science 2024, 7: 317-343. PMID: 39178425, PMCID: PMC11346580, DOI: 10.1146/annurev-biodatasci-120423-120107.Peer-Reviewed Original ResearchConceptsPrivacy-enhancing technologiesAdoption of privacy-enhancing technologiesBiomedical data scienceData scienceAnalyze sensitive dataBiomedical data repositoriesPrivacy protectionSensitive dataPrivacy concernsData silosProtect privacyHuman subject dataBiomedical domainData repositoriesPrivacySubjective dataConventional framework
2023
sfkit: a web-based toolkit for secure and federated genomic analysis.
Mendelsohn S, Froelicher D, Loginov D, Bernick D, Berger B, Cho H. sfkit: a web-based toolkit for secure and federated genomic analysis. Nucleic Acids Research 2023, 51: w535-w541. PMID: 37246709, PMCID: PMC10320181, DOI: 10.1093/nar/gkad464.Peer-Reviewed Original ResearchConceptsCommand line interfaceGroup of collaboratorsCryptographic techniquesPrivacy concernsCollaborative workflowsUse casesWeb-based toolkitWeb serverComputational environmentCollaborative toolsMultiple partiesEssential taskDatasetServerPrivacyGenomic data collectionPrincipal component analysisToolkitData collectionWorkflowToolTaskComponent analysisRecent workComplexity
2021
Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption
Froelicher D, Troncoso-Pastoriza J, Raisaro J, Cuendet M, Sousa J, Cho H, Berger B, Fellay J, Hubaux J. Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption. Nature Communications 2021, 12: 5910. PMID: 34635645, PMCID: PMC8505638, DOI: 10.1038/s41467-021-25972-y.Peer-Reviewed Original ResearchConceptsMultiparty homomorphic encryptionHomomorphic encryptionPrivacy-preserving analysisNecessary key stepMultiple healthcare institutionsFederated analyticsFederated settingAnalysis tasksAnalytics systemIntermediate dataEncryptionCentralized studiesPatient dataBiomedical insightsScientific collaborationAccurate resultsIndispensable complementAnalyticsHealthcare institutionsDatasetTaskSystemBiomedical researchAccessCollaborationPrivacy-preserving genotype imputation in a trusted execution environment
Dokmai N, Kockan C, Zhu K, Wang X, Sahinalp S, Cho H. Privacy-preserving genotype imputation in a trusted execution environment. Cell Systems 2021, 12: 983-993.e7. PMID: 34450045, PMCID: PMC8542641, DOI: 10.1016/j.cels.2021.08.001.Peer-Reviewed Original ResearchConceptsTrusted Execution EnvironmentExecution environmentHardware-based solutionsSide-channel attacksIntel SGXEnhanced securityPrivacy concernsAnalysis servicesImputation ServerServer limitData resourcesImputation algorithmSGXServerImputation softwareGenomic data resourcesImputation accuracyGenotype imputationImputation strategiesServicesDownstream analysisScalabilityImputationEssential toolSecurity
2020
Privacy-Preserving Biomedical Database Queries with Optimal Privacy-Utility Trade-Offs
Cho H, Simmons S, Kim R, Berger B. Privacy-Preserving Biomedical Database Queries with Optimal Privacy-Utility Trade-Offs. Cell Systems 2020, 10: 408-416.e9. PMID: 32359425, DOI: 10.1016/j.cels.2020.03.006.Peer-Reviewed Original ResearchConceptsDifferential privacySensitive individual-level dataFormal privacy guaranteesQuery-answering systemPrivacy-utility tradePrivacy guaranteesQuery answersCount queriesCohort discoveryDatabase queriesUtility functionUse casesProof of optimalityResearch workflowAggregate insightsBiomedical databasesAccuracy improvementPrivate informationQueriesPrivacyGeneral utility functionDatabaseMore general utility functionsNew theoretical resultsLookup