A UAV-Assisted Truth Discovery Approach with Incentive Mechanism Design in Mobile Crowd Sensing

Incentive mechanisms are essential to incentive workers carrying mobile handheld devices to participate in mobile crowd sensing and finally achieve good truth discovery performance. However, malicious workers may report false or malicious data to defraud rewards, resulting in service quality degradation. Moreover, the existing incentive mechanism is challenging to identify malicious workers when recruiting workers in reality, which results in low accuracy of truth discovery and waste of cost. In this paper, we propose an Incentive-based Truth Discovery (ITD) scheme to incentive credible workers to submit high-quality data, thereby enhancing the accuracy of truth discovery. In the ITD, an unmanned aerial vehicle (UAV)-assisted split-aggregation truth discovery mechanism is proposed firstly to infer the truth. The addition of the UAV can improve the accuracy of truth discovery and assist in evaluating workers' trust. Then, we evaluate the quality of participants' data and propose a data quality-based trust meter to update each worker's trust to guide future recruitment efforts. Finally, a Quality-aware Trustworthy Incentive (QTI) mechanism is proposed to select credible workers for data collection and provide them with reasonable payments. The experimental results show that ITD improves the accuracy of truth discovery by 98.47%, over the state-of-the-art, at a sensing cost reduced by as high as 43.89%.