On the privacy offered by (k, delta)-anonymity
The widespread deployment of technologies with tracking capabilities, like GPS, GSM, RFID and on-line social networks, allows mass collection of spatio-temporal data about their users. As a consequence, several methods aimed at anonymizing spatio-temporal data before their publication have been proposed in recent years. Such methods are based on a number of underlying privacy models. Among these models, (k,delta)-anonymity claims to extend the widely used k-anonymity concept by exploiting the spatial uncertainty delta >= 0 in the trajectory recording process. In this paper, we prove that, for any delta > 0 (that is, whenever there is actual uncertainty), (k,delta)-anonymity does not offer trajectory k-anonymity, that is, it does not hide an original trajectory in a set of k indistinguishable anonymized trajectories. Hence, the methods based on (k,delta)-anonymity, like Never Walk Alone (NWA) and Wait For Me (W4M) can offer trajectory k-anonymity only when delta = 0 (no uncertainty). Thus, the idea of exploiting the recording uncertainty delta to achieve trajectory k-anonymity with information loss inversely proportional to delta turns out to be flawed. (C) 2012 Elsevier Ltd. All rights reserved.
anonymity spatio-temporal data uncertainty trajectory data privacy