In this paper, we tackle the problem of collecting individual trajectories under local
differential privacy. The key challenge is how to achieve high utility of the collected …

Trajectory data collection is a common task with many applications in our daily lives.
Analyzing trajectory data enables service providers to enhance their services, which …

Trajectory data has the potential to greatly benefit a wide-range of real-world applications,
such as tracking the spread of the disease through people's movement patterns and …

Trajectory data, ie, human mobility traces, is extremely valuable for a wide range of mobile
applications. However, publishing raw trajectories without special sanitization poses serious …

With the ubiquity of Internet of Things, location-based service (LBS) providers have collected
huge volumes of individuals' trajectories, which are valuable for some applications, eg, store …

Ubiquitous deployment of low-cost mobile positioning devices and the widespread use of
high-speed wireless networks enable massive collection of large-scale trajectory data of …

Vehicle trajectory data is critical for traffic management and location-based services.
However, the released trajectories raise serious privacy concerns because they contain …

Mobile devices have been an integral part of our everyday lives. Users' increasing
interaction with mobile devices brings in significant concerns on various types of potential …

Privacy-preserving spatio-temporal data sharing is vital in many machine learning and
analysis tasks, such as managing disease spread or tailoring public services to a …

With the popularity of location-aware devices (eg, smart phones), a large number of
trajectory data were collected. The trajectory dataset can be used in many fields including …