IoT data markets in public and private institutions have become increasingly relevant in
recent years because of their potential to improve data availability and unlock new business …

With the proliferation of social sensing, large amounts of observation are contributed by
people or devices. However, these observations contain disinformation. Disinformation can …

Federated deep learning has been widely used in various fields. To protect data privacy,
many privacy-preservingapproaches have been designed and implemented in various …

Truth discovery has received considerable attention in mobile crowdsensing systems. In real
practice, it is vital to resolve conflicts among a large amount of sensory data and estimate the …

Many real-world social networks are decentralized in nature, and the only way to analyze
such a network is to collect local views of the social graph from individual participants. Since …

Incentive mechanisms are essential for stimulating adequate worker participation to achieve
good truth discovery performance in mobile crowdsensing (MCS) systems. However, most of …

Truth discovery is an effective paradigm which could reveal the truth from crowdsouced data
with conflicts, enabling data-driven decision-making systems to make quick and smart …

The crowd's power, combined with the sensing capabilities of smart mobile de-vices, has
resulted in the emergence of a revolutionary data acquisition paradigm known as Mobile …

Benefitingfrom the rapid development of communication technology and Internet of Things
(IoT) devices, crowdsensing is on the rise. Sensor data from IoT devices can be requested …

To obtain reliable results from conflicting data in mobile crowdsensing, numerous truth
discovery protocols have been proposed in the past decade. However, most of them do not …