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Evaluating data utility of
privacy-preserving pseudonymized location datasets {tanjo, kminami, hm2}@ism.ac.jp 2NTT
Corporation, Kanagawa, Japan mano.ken@lab.ntt.co.jp Abstract Pseudonymization
is an effective way to publish a location dataset with trajectory information
in a privacy-preserving way. We previously proposed a technique of randomly
exchanging multiple users¡¯ pseudonyms at a mix zone where the users meet at
the same time to prevent an adversary from reidentifying multiple trajectory
segments of a target user. However, such a segmentation technique essentially
divides a user¡¯s whole trajectory path into multiple segments and thus
degrades the utility of the dataset. In this paper, we, therefore, evaluate
tradeoffs between data utility and privacy by conducting various experiments
with a real location dataset. Our experimental results show that it is possible
to achieve sufficient data utility while satisfying realistic privacy
requirements. Keywords: location privacy, dynamic pseudonym, constraint satisfaction problem. +: Corresponding author: Tomoya Tanjo The Institute of
Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan, Journal of
Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications
(JoWUA), Vol. 5, No. 3,
pp. 63-78, September 2014 [pdf] |