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The study by De Montjoye et al. ("Science", 30 January 2015, p. 536) claimedthat most individuals can be reidentified from a deidentified credit cardtransaction database and that anonymization mechanisms are not effectiveagainst reidentification. Such claims deserve detailed quantitative scrutiny,as they might seriously undermine the willingness of data owners and subjectsto share data for research. In a recent Technical Comment published in"Science" (18 March 2016, p. 1274), we demonstrate that the reidentificationrisk reported by De Montjoye et al. was significantly overestimated (due to amisunderstanding of the reidentification attack) and that the allegedineffectiveness of anonymization is due to the choice of poor and undocumentedmethods and to a general disregard of 40 years of anonymization literature. Thetechnical comment also shows how to properly anonymize data, in order to reduceunequivocal reidentifications to zero while retaining even more analyticalutility than with the poor anonymization mechanisms employed by De Montjoye etal. In conclusion, data owners, subjects and users can be reassured that soundprivacy models and anonymization methods exist to produce safe and usefulanonymized data.  Supplementary materials detailing the data sets, algorithms and extendedresults of our study are available here. Moreover, unlike the De Montjoye etal.'s data set, which was never made available, our data, anonymized results,and anonymization algorithms can be freely downloaded fromhttp://crises-deim.urv.cat/opendata/SPD_Science.zip

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Supplementary Materials for "How to Avoid Reidentification with Proper  Anonymization"- Comment on "Unique in the shopping mall: on the  reidentifiability of credit card metadata"