The continuous publication of aggregate statistics over crowd-sourced data to the public has
enabled many data mining applications (eg, real-time traffic analysis). Existing systems …

Nowadays gigantic crowd-sourced data collected from mobile phone users have become
widely available, which enables the possibility of many important data mining applications to …

Nowadays gigantic crowd-sourced data from mobile devices have become widely available
in social networks, enabling the possibility of many important data mining applications to …

High-dimensional crowdsourced data collected from numerous users produces rich
knowledge about our society; however, it also brings unprecedented privacy threats to the …

In this paper, we study the problem of publishing high-dimensional data in a distributed multi-
party environment under differential privacy. In particular, with the assistance of a semi …

Internet of Things and the related computing paradigms, such as cloud computing and fog
computing, provide solutions for various applications and services with massive and high …

The massive generation, extensive sharing, and deep exploitation of data in the big data era
have raised unprecedented privacy threats. To address privacy concerns, various privacy …

Trajectory data is valuable for various applications, especially for intelligent transportation
systems, which hunger for plenty of trajectories. However, publishing trajectory data while …

Along with the generation of Internet of Things (IoT), the values of tremendous volumes of
sensing data will be slowly unlocked. Thus, crowd-sensed data trading as a new business …

Collecting and analyzing massive data generated from smart devices have become
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …