Privacy-Preserving Opt-Out from Homomorphically Encrypted Clinical Trials...23rd International Conference on Informatics, Management and Technology in Healthcare (ICIMTH 2025), July 4-6, 2025, Athens, Greece.
Data protection regulations, such as the GDPR, ensure individuals' rights regarding processing of their personal data, including the 'right to be forgotten,' which mandates the opt-out and deletion of personal data from datasets at any stage. Homomorphic encryption enables arithmetic operations on e...
| Publicado en: | Studies in Health Technology & Informatics Vol. 328; pp. 505 - 510 |
|---|---|
| Autores principales: | , , , |
| Formato: | proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2025
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=186368455&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 186368455 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2025 vid: 328 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 186368455 186368455 186368455 10.3233/SHTI250771 186368455 ppf: 505 ppct: 5 formats: tig: atl: Privacy-Preserving Opt-Out from Homomorphically Encrypted Clinical Trials...23rd International Conference on Informatics, Management and Technology in Healthcare (ICIMTH 2025), July 4-6, 2025, Athens, Greece. aug: au: PUSKARIC, Miroslav GUSINOW, Roy GÓRSKA, Anna HASENAUER, Jan affil: HLRS - High Performance Computing Center Stuttgart, University of Stuttgart, Germany sug: subj: Privacy and Confidentiality Clinical Trials Encryption Data Security Artificial Intelligence Health Informatics Electronic Health Records Congresses and Conferences Greece Greece Human Data Management Methods Conceptual Framework Software Design Patient Attitudes Treatment Refusal Patient Participation Psychosocial Factors Data Collection Information Storage ab: Data protection regulations, such as the GDPR, ensure individuals' rights regarding processing of their personal data, including the 'right to be forgotten,' which mandates the opt-out and deletion of personal data from datasets at any stage. Homomorphic encryption enables arithmetic operations on encrypted numerical vectors while keeping the data and intermediate results hidden throughout the analysis process. This paper presents an implementation of the right to be forgotten using homomorphic encryption, designed for a real-world use case involving the collection and storage of clinical data in an international collaboration. We introduce methods for structuring data as collections of encrypted vectors and propose algorithms for privacy-preserving opt-out and verifiable data deletion. These algorithms are implemented and tested in a software prototype, with a performance analysis of their computational efficiency. Our approach provides a framework for patient withdrawal at any stage of a clinical trial, balancing the need for data privacy with the computational constraints of homomorphic encryption by structuring clinical datasets into encrypted vector collections. pubtype: Academic Journal doctype: proceedings research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|