Abstract
Many applications benefit from user location data, but location data raises privacy concerns. Anonymization can protect privacy, but identities can sometimes be inferred from supposedly anonymous data. This paper studies a new attack on the anonymity of location data. We show that if the approximate locations of an individual’s home and workplace can both be deduced from a location trace, then the median size of the individual’s anonymity set in the U.S. working population is 1, 21 and 34,980, for locations known at the granularity of a census block, census track and county respectively. The location data of people who live and work in different regions can be re-identified even more easily. Our results show that the threat of re-identification for location data is much greater when the individual’s home and work locations can both be deduced from the data. To preserve anonymity, we offer guidance for obfuscating location traces before they are disclosed.
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© 2009 Springer-Verlag Berlin Heidelberg
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Golle, P., Partridge, K. (2009). On the Anonymity of Home/Work Location Pairs. In: Tokuda, H., Beigl, M., Friday, A., Brush, A.J.B., Tobe, Y. (eds) Pervasive Computing. Pervasive 2009. Lecture Notes in Computer Science, vol 5538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01516-8_26
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DOI: https://doi.org/10.1007/978-3-642-01516-8_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01515-1
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