The spatial crowdsourcing task places workers at a risk of privacy leakage. If positional
information is not required to submit, it will result in an increased error rate and number of …

As one of the most fundamental problems in mobile crowdsensing (MCS), worker selection
has drawn significant attention in recent years. However, very few studies consider the …

Recently, the development of Internet of Things and mobile sensor technology has facilitated
mobile crowdsensing (MCS) as a popular data collection paradigm. In MCS, requesters …

With the rapid development in mobile devices, mobile crowdsourcing has become an
important research focus. In large-scale mobile crowdsourcing, the effective evolution …

With the popularization of intelligent terminals, especially current trends, such as “Industrie
4.0” and the Internet of Things, mobile crowdsensing is becoming one of the promising …

The key pillar of developing digital city is the ubiquitous sensing of people and the
environment. Crowdsensing requires a large number of users to participate in the collection …

With the rapid popularization and development of the Internet of Things (IoT) and 5G
networks, mobile crowdsourcing (MCS) has become an indispensable part in today's …

Mobile Crowdsensing (MCS) has become an effective technology for urban data sensing
and acquisition. But this also brings the risk of trajectory privacy disclosure for participants …

Mobile Crowdsensing (MCS) is a paradigm for collecting large-scale sensor data by
leveraging mobile devices equipped with small and low-powered sensors. MCS has …

Nowadays, vehicles have been increasingly adopted in many spatial crowdsourcing (SC)
applications. Similar to other SC applications, location privacy is of great concern to vehicle …