Advances in artificial intelligence (AI) have shaped today's user services, enabling
enhanced personalization and better support. As such AI-based services inevitably require …

In conventional mobile crowdsensing (MCS) applications, the crowdsensing server (CS-
server) needs mobile users' precise locations for optimal task allocation, which raises …

User services increasingly base their actions on AI models, eg, to offer personalized and
proactive support. However, the underlying AI algorithms require a continuous stream of …

The exponential increase in the availability of large-scale mobility data has fueled the vision
of smart cities that will transform our lives. The truth is that we have just scratched the surface …

Smartphones are nowadays the dominant end-user device. As a result, they have become
gateways to all users' communications, including sensitive personal data. In this paper, we …

The incorporation of the mobile crowd in visual sensing provides a significant opportunity to
explore and understand uncharted physical places. We investigate the gains and losses of …

With the enormous popularity of smartphones, millions of mobile apps are developed to
provide rich functionalities for users by accessing certain personal data, leading to great …

Recently, the ubiquity of mobile devices leads to an increasing demand of public network
services, eg, WiFi hot spots. As a part of this trend, modern transportation systems are …

While past research has explored the effects of different targeted promotion strategies (eg,
temporal, geographical, crowdedness-based), it is yet to take into account the effect of social …

Some credible third parties collect and share mobile sensor data with users to enhance
scientific innovation. However, since the sensor data contains sensitive attributes, it may …