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Using Secure Multi-Party Computation to Create Clinical Trial Cohorts

2025-12-24Artigo científico Acesso aberto
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datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.fosCiências Médicas::Ciências da Saúde
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorBorges, Rafael
dc.contributor.authorFerreira, Bruno
dc.contributor.authorAntunes, Carlos Machado
dc.contributor.authorMaximiano, Marisa
dc.contributor.authorGomes, Ricardo
dc.contributor.authorTávora, Vitor
dc.contributor.authorDias, Manuel
dc.contributor.authorBezerra, Ricardo Correia
dc.contributor.authorDomingues, Patrício
dc.contributor.editorAntunes, Carlos Machado
dc.date.accessioned2026-01-20T15:49:49Z
dc.date.available2026-01-20T15:49:49Z
dc.date.issued2025-12-24
dc.descriptionArticle number 2.
dc.descriptionThis article belongs to the Special Issue Cyber Security and Digital Forensics—2nd Edition.
dc.descriptionAcknowledgments: This work is included in the Blockchain.pt project, part of Portugal’s Recovery and Resilience Plan with the objective of spreading blockchain to various sectors and it was done in partnership with BioGHP (https://www.bioghp.com/, accessed on 25 July 2025).
dc.description.abstractThe increasing volume of digital medical data offers substantial research opportunities, though its complete utilization is hindered by ongoing privacy and security obstacles. This proof-of-concept study explores and confirms the viability of using Secure Multi-Party Computation (SMPC) to ensure protection and integrity of sensitive patient data, allowing the construction of clinical trial cohorts. Our findings reveal that SMPC facilitates collaborative data analysis on distributed, private datasets with negligible computational costs and optimized data partition sizes. The established architecture incorporates patient information via a blockchain-based decentralized healthcare platform and employs the MPyC library in Python for secure computations on Fast Healthcare Interoperability Resources (FHIR)-format data. The outcomes affirm SMPC’s capacity to maintain patient privacy during cohort formation, with minimal overhead. It illustrates the potential of SMPC-based methodologies to expand access to medical research data. A key contribution of this work is eliminating the need for complex cryptographic key management while maintaining patient privacy, illustrating the potential of SMPC-based methodologies to expand access to medical research data by reducing implementation barriers.eng
dc.description.sponsorshipThis work was financially supported by Project BlockchainPT—Decentralize Portugal with Blockchain Agenda, WP2: Health and Wellbeing, 02/C05-i01.01/2022.PC644918095-00000033, funded by the Portuguese Recovery and Resilience Program (PPR) (https://recuperarportugal.gov.pt/, accessed on 25 July 2025), The Portuguese Republic and The European Union (EU) under the framework of Next Generation EU Program.
dc.identifier.citationBorges, R., Ferreira, B., Antunes, C. M., Maximiano, M., Gomes, R., Távora, V., Dias, M., Bezerra, R. C., & Domingues, P. (2026). Using Secure Multi-Party Computation to Create Clinical Trial Cohorts. Journal of Cybersecurity and Privacy, 6(1), 2. https://doi.org/10.3390/jcp6010002
dc.identifier.doi10.3390/jcp6010002
dc.identifier.issn2624-800X
dc.identifier.urihttp://hdl.handle.net/10400.8/15420
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.relation.hasversionhttps://www.mdpi.com/2624-800X/6/1/2
dc.relation.ispartofJournal of Cybersecurity and Privacy
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectSecure Multi-Party Computation
dc.subjectPrivacy
dc.subjectElectronic Health Records
dc.subjectPrivate data sharing
dc.subjectHealthcare
dc.titleUsing Secure Multi-Party Computation to Create Clinical Trial Cohortseng
dc.typejournal article
dcterms.referenceshttps://github.com/AgendaBlockchain-IPLeiria/CHIQ-SMPC-Data/
dspace.entity.typePublication
oaire.citation.endPage21
oaire.citation.issue1
oaire.citation.startPage1
oaire.citation.titleJournal of Cybersecurity and Privacy
oaire.citation.volume6
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.affiliation.nameCIIC / ESTG
person.affiliation.nameESTG
person.familyNameBorges
person.familyNameMachado Antunes
person.familyNameMaximiano
person.familyNamePereira Gomes
person.familyNameTávora
person.familyNameDomingues
person.givenNameRafael
person.givenNameCarlos
person.givenNameMarisa
person.givenNameRicardo Jorge
person.givenNameVitor
person.givenNamePatrício
person.identifierurn:authenticus_id:R-002-SEG
person.identifier.ciencia-idA919-B117-A16D
person.identifier.ciencia-id2319-A0CE-6813
person.identifier.ciencia-idAA15-6185-C477
person.identifier.gsid6gzjmMkAAAAJ
person.identifier.orcid0009-0006-7001-8048
person.identifier.orcid0009-0005-7010-4328
person.identifier.orcid0000-0002-1212-7864
person.identifier.orcid0000-0002-0438-9119
person.identifier.orcid0009-0004-0404-9378
person.identifier.orcid0000-0002-6207-6292
person.identifier.ridADM-8923-2022
person.identifier.scopus-author-id26767664900
person.identifier.scopus-author-id57413754100
person.identifier.scopus-author-id13411315400
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