Study on Record Linkage of Anonymizied Data

SUMMARY 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 competitionforthebestanonymizationandre-identificationalgorithm. 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. key words: data privacy, anonymization, re-identification risk, big data

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