Unique in the shopping mall: On the reidentifiability of credit card metadata
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UniqueInTheShoppingMall_draft.pdf
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569.49 KB
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Author(s)
Radaelli, L.
de Montjoye, Yves-Alexandre
Singh, Vivek Kumar
Pentland, Alex Paul
Date Issued
January 2015
Journal
Science
Publisher
American Association for the Advancement of Science (AAAS)
Citation
De Montjoye, Y.-A., L. Radaelli, V. K. Singh, and A. Pentland. “Unique in the Shopping Mall: On the Reidentifiability of Credit Card Metadata.” Science 347, no. 6221 (January 29, 2015): 536–539.
Version
Author's final manuscript
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
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1126/science.1256297
