On the Anonymity of Home/Work Location Pairs
P. Golle. and K. Partridge.
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 guidelines for obfuscating
location traces before they are disclosed.