Privacy-aware Incentive Mechanism Framework for Mobile Crowdsensing
Shaojun Zhu, Dan Tao · 2019
The large-scale deployment of mobile sensing tasks can be hindered by the lack of effective incentives for users to participate and protection of users' privacy. In this paper, we propose a novel privacy-aware incentive mechanism framework by introducing a third party as an arbitration center to separate the relevance between users and task data, and thus protect users' privacy. Finally, we evaluate the proposed solution by function verification. Extensive experimental results demonstrate the effectiveness of our solution that contribute to user privacy protection.