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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
Publication Date: 2018/01/01
Online ISSN: 1745-1337
Type of Manuscript: 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.