Unique in the shopping mall: On the reidentifiability of credit card metadata

Yves Alexandre De Montjoye, Laura Radaelli, Vivek Kumar Singh, Alex Sandy Pentland

Research output: Contribution to journalArticlepeer-review

296 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)536-539
Number of pages4
Issue number6221
StatePublished - Jan 30 2015

All Science Journal Classification (ASJC) codes

  • General


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