Cristin-resultat-ID: 1425857
Sist endret: 30. mai 2017 10:58
NVI-rapporteringsår: 2017
Resultat
Vitenskapelig artikkel
2017

Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computation

Bidragsytere:
  • Kassaye Yitbarek Yigzaw
  • Antonis Michalas og
  • Johan Gustav Bellika

Tidsskrift

BMC Medical Informatics and Decision Making
ISSN 1472-6947
e-ISSN 1472-6947
NVI-nivå 1

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2017
Publisert online i 2017
Volum: 17
Hefte: 1
Side(r):
1
-
19
Open Access

Importkilder

Scopus-ID: 2-s2.0-85010022724

Finansiering

  • Norges forskningsråd

    • Prosjektkode: 174934
    • Prosjektkode: 248150

Beskrivelse Beskrivelse

Tittel

Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computation

Sammendrag

Background: Techniques have been developed to compute statistics on distributed datasets without revealing private information except the statistical results. However, duplicate records in a distributed dataset may lead to incorrect statistical results. Therefore, to increase the accuracy of the statistical analysis of a distributed dataset, secure deduplication is an important preprocessing step. Methods: We designed a secure protocol for the deduplication of horizontally partitioned datasets with deterministic record linkage algorithms. We provided a formal security analysis of the protocol in the presence of semi-honest adversaries. The protocol was implemented and deployed across three microbiology laboratories located in Norway, and we ran experiments on the datasets in which the number of records for each laboratory varied. Experiments were also performed on simulated microbiology datasets and data custodians connected through a local area network. Results: The security analysis demonstrated that the protocol protects the privacy of individuals and data custodians under a semi-honest adversarial model. More precisely, the protocol remains secure with the collusion of up to N − 2 corrupt data custodians. The total runtime for the protocol scales linearly with the addition of data custodians and records. One million simulated records distributed across 20 data custodians were deduplicated within 45 s. The experimental results showed that the protocol is more efficient and scalable than previous protocols for the same problem. Conclusions: The proposed deduplication protocol is efficient and scalable for practical uses while protecting the privacy of patients and data custodians.

Bidragsytere

Kassaye Yitbarek Yigzaw

  • Tilknyttet:
    Forfatter
    ved Fakultet for naturvitenskap og teknologi ved UiT Norges arktiske universitet
  • Tilknyttet:
    Forfatter
    ved Nasjonalt senter for e-helseforskning ved Universitetssykehuset Nord-Norge HF

Antonis Michalas

  • Tilknyttet:
    Forfatter
    ved University of Westminster

Johan Gustav Bellika

  • Tilknyttet:
    Forfatter
    ved Nasjonalt senter for e-helseforskning ved Universitetssykehuset Nord-Norge HF
  • Tilknyttet:
    Forfatter
    ved Telemedisin og e-helse ved UiT Norges arktiske universitet
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