Study on Record Linkage of Anonymizied Data

Hiroaki KIKUCHI  Takayasu YAMAGUCHI  Koki HAMADA  Yuji YAMAOKA  Hidenobu OGURI  Jun SAKUMA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E101-A    No.1    pp.19-28
Publication Date: 2018/01/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E101.A.19
Type of Manuscript: Special Section INVITED PAPER (Special Section on Cryptography and Information Security)
data privacy,  anonymization,  re-identification risk,  big data,  

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Data anonymization is required before a big-data business can run effectively without compromising the privacy of personal information it uses. It is not trivial to choose the best algorithm to anonymize some given data securely for a given purpose. In accurately assessing the risk of data being compromised, there needs to be a balance between utility and security. Therefore, using common pseudo microdata, we propose a competition for the best anonymization and re-identification algorithm. The paper reported the result of the competition and the analysis on the effective of anonymization technique. The competition result reveals that there is a tradeoff between utility and security, and 20.9% records were re-identified in average.