2017
DOI: 10.1186/s12911-016-0389-x
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Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computation

Abstract: BackgroundTechniques 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.MethodsWe designed a secure protocol for the deduplication of horizontally partitioned datasets with deterministic re… Show more

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Cited by 80 publications
(75 citation statements)
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References 59 publications
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“…The latter can be more effective when dealing with complex records, such as those with a lot of missing data or coding errors. 15 16 …”
Section: Discussionmentioning
confidence: 99%
“…The latter can be more effective when dealing with complex records, such as those with a lot of missing data or coding errors. 15 16 …”
Section: Discussionmentioning
confidence: 99%
“…A number of systems combine self-management and telemonitoring [ 20 , 103 ]. Most of them focus on enabling patients to self-assess their status (see Sect.…”
Section: Existing Devices and Technologies Suitable For The Remote Anmentioning
confidence: 99%
“…The protocol proposed in [83] achieved better scalability using third partyaided computation model. In general, these protocols exchange messages that have smaller sizes the protocols proposed in [78][79][80].…”
Section: Privacy-preserving Record Linkagementioning
confidence: 99%
“…Multi-party [81][82][83] and two-party [84] protocols are also proposed for deterministic record linkage based on Bloom filter. In these protocols, each data custodian encodes its identifiers as a Bloom filter, and the data custodians use different mechanisms to securely compute the intersection between their Bloom filters.…”
Section: Privacy-preserving Record Linkagementioning
confidence: 99%