Unique in the shopping mall: On the reidentifiability of credit card metadata
Top Cited Papers
- 30 January 2015
- journal article
- Published by American Association for the Advancement of Science (AAAS) in Science
- Vol. 347 (6221), 536-539
- https://doi.org/10.1126/science.1256297
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.Keywords
Funding Information
- Belgian American Educational Foundation
- Army Research Laboratory (W911NF-09-2-0053)
- European Commission
- FP7-People Marie Curie Action (264994)
- Wallonie-Bruxelles International
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