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Author Christen, Peter ♦ Vatsalan, Dinusha ♦ Verykios, Vassilios S
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Privacy techniques ♦ Data matching ♦ Privacy-preserving record linkage
Abstract Techniques for integrating data from diverse sources have attracted significant interest in recent years. Much of today’s data collected by businesses and governments are about people, and integrating such data across organizations can raise privacy concerns. Various techniques that preserve privacy during data integration have been developed, but several challenges persist that need to be solved before such techniques become useful in practical applications. We elaborate on these challenges and discuss research directions.
ISSN 19361955
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-09-04
Publisher Place New York
e-ISSN 19361963
Journal Journal of Data and Information Quality (JDIQ)
Volume Number 5
Issue Number 1-2
Page Count 3
Starting Page 1
Ending Page 3


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Source: ACM Digital Library