Crowdsensing-based mobile Internet, while facilitating users' daily life, also raises privacy
concerns because of sharing user location trajectories. Combining with open-source …

The increasing popularity of smartphones and location-based service (LBS) has brought us
a new experience of mobile crowdsourcing marked by the characteristics of network …

Synthesizing a fake trajectory with consistent lifestyle and meaningful mobility as the actual
one is the most popular way to protect the location privacy in trajectory sharing. Recent …

For academic research and business intelligence, trajectory data has been widely collected
and analyzed. Releasing trajectory data to a third party may lead to serious privacy leakage …

Mobile communication services raise user privacy concerns in sharing the traveling
trajectories while facilitating people's daily lives. According to these shared trajectories …

The boom of mobile devices and location-based services (LBSs) greatly enriches the mobile
social network (MSN) applications, which bring convenience to our daily life and …

It is crucial to protect users' location traces against inference attacks on aggregate mobility
data collected from multiple users in various real-world applications. Most of the existing …

Due to the popularity of mobile computing and mobile sensing, users' traces can now be
readily collected to enhance applications' performance. However, users' location privacy …

Generating human mobility trajectories is of great importance to solve the lack of large-scale
trajectory data in numerous applications, which is caused by privacy concerns. However …

Along with the popularity of mobile social networks (MSNs) is the increasing danger of
privacy breaches due to user location exposures. In this work, we take an initial step towards …