Privacy-preserving record linkage

Dinusha Vatsalan*, Dimitrios Karapiperis, Vassilios Verykios, Sherif Sakr and Albert Zomaya

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Given several databases containing person-specific data held by different organizations, privacy-preserving record linkage (PPRL) aims to identify and link records that correspond to the same entity/individual across different databases based on the matching of personal identifying attributes, such as name and address, without revealing the actual values in these attributes due to privacy concerns. The output is a set of matching clusters containing records of the same entity.
Original languageEnglish
Title of host publicationEncyclopedia of Big Data Technologies
EditorsSherif Sakr, Albert Zomaya
Place of PublicationCham, Switzerland
PublisherSpringer, Springer Nature
Pages1-8
Number of pages8
EditionLiving Edition
ISBN (Electronic)9783319639628
DOIs
Publication statusPublished - 7 Feb 2018
Externally publishedYes

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