Unique in the shopping mall: On the reidentifiability of credit card metadata
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Unique in the shopping mall- On the reidentifiability of credit card metadata.pdf
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696.25 KB
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Author(s)
de Montjoye, Yves-Alexandre
Radaelli, Laura
Singh, Vivek Kumar
Pentland, Alex
Date Issued
January 30, 2015
Publisher
Science
Citation
De Montjoye, Y. A., Radaelli, L., Singh, V. K., & Pentland, A. (2015). Unique in the shopping mall: On the reidentifiability of credit card metadata. Science, 347(6221), 536-539.
Abstract
Large-scale data sets of human behavior have the potential to fundamentally transform the way we fight diseases, design cities, or perform research. Metadata, however, contain sensitive information. Understanding the privacy of these data sets is key to their broad use and, ultimately, their impact. We study 3 months of credit card records for 1.1 million people and show that four spatiotemporal points are enough to uniquely reidentify 90% of individuals. We show that knowing the price of a transaction increases the risk of reidentification by 22%, on average. Finally, we show that even data sets that provide coarse information at any or all of the dimensions provide little anonymity and that women are more reidentifiable than men in credit card metadata.
MIT Department
MIT Connection Science (Research institute)
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Attribution-NonCommercial-ShareAlike 3.0 United States
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