相关论文: On the Anonymization of Differentially Private Loc…
In pervasive computing environments, Location- Based Services (LBSs) are becoming increasingly important due to continuous advances in mobile networks and positioning technologies. Nevertheless, the wide deployment of LBSs can jeopardize…
Location privacy-preserving mechanisms (LPPMs) have been extensively studied for protecting a user's location at each time point or a sequence of locations with different timestamps (i.e., a trajectory). We argue that existing LPPMs are not…
We consider the problem of privacy-preserving data release for a specific utility task under perfect obfuscation constraint. We establish the necessary and sufficient condition to extract features of the original data that carry as much…
Many popular applications use traces of user data to offer various services to their users. However, even if user data is anonymized and obfuscated, a user's privacy can be compromised through the use of statistical matching techniques that…
News reports of the last few years indicated that several intelligence agencies are able to monitor large networks or entire portions of the Internet backbone. Such a powerful adversary has only recently been considered by the academic…
In this paper, we design user-centric obfuscation mechanisms that impose the minimum utility loss for guaranteeing user's privacy. We optimize utility subject to a joint guarantee of differential privacy (indistinguishability) and…
When it comes to location-based services (LBS), user privacy protection can be in conflict with security of both users and trips. While LBS providers could adopt privacy preservation mechanisms to obfuscate customer data, the accuracy of…
Geo-indistinguishability and expected inference error are two complementary notions for location privacy. The joint guarantee of differential privacy (indistinguishability) and distortion privacy (inference error) limits the information…
Local differential privacy (LPD) is a distributed variant of differential privacy (DP) in which the obfuscation of the sensitive information is done at the level of the individual records, and in general it is used to sanitize data that are…
LDP (Local Differential Privacy) has been widely studied to estimate statistics of personal data (e.g., distribution underlying the data) while protecting users' privacy. Although LDP does not require a trusted third party, it regards all…
For real-world mobile applications such as location-based advertising and spatial crowdsourcing, a key to success is targeting mobile users that can maximally cover certain locations in a future period. To find an optimal group of users,…
While becoming more and more present in our every day lives, services that operate on users' locations or location trajectories suffer from general fear of misappropriation of the transmitted location data. Several works have investigated…
In recent years, the widespread of mobile devices equipped with GPS and communication chips has led to the growing use of location-based services (LBS) in which a user receives a service based on his current location. The disclosure of…
Shortest path computation is one of the most common queries in location-based services (LBSs). Although particularly useful, such queries raise serious privacy concerns. Exposing to a (potentially untrusted) LBS the client's position and…
Location-based Services (LBSs) provide valuable services, with convenient features for users. However, the information disclosed through each request harms user privacy. This is a concern particularly with honest-but-curious LBS servers,…
Due to the pervasiveness of image capturing devices in every-day life, images of individuals are routinely captured. Although this has enabled many benefits, it also infringes on personal privacy. A promising direction in research on…
We introduce a general model for the local obfuscation of probability distributions by probabilistic perturbation, e.g., by adding differentially private noise, and investigate its theoretical properties. Specifically, we relax a notion of…
Researchers face the trade-off between publishing mobility data along with their papers while simultaneously protecting the privacy of the individuals. In addition to the fundamental anonymization process, other techniques, such as spatial…
In recent years, it has become easy to obtain location information quite precisely. However, the acquisition of such information has risks such as individual identification and leakage of sensitive information, so it is necessary to protect…
With current technology, a number of entities have access to user mobility traces at different levels of spatio-temporal granularity. At the same time, users frequently reveal their location through different means, including geo-tagged…