Department of Computer Engineering, Myongji University, Yongin 17058, Korea.
Department of Information and Communication Engineering, Myongji University, Yongin 17058, Korea.
Sensors (Basel). 2021 Oct 24;21(21):7045. doi: 10.3390/s21217045.
Crowdsensing systems have been developed for wide-area sensing tasks because humancarried smartphones are prevailing and becoming capable. To encourage more people to participate in sensing tasks, various incentive mechanisms were proposed. However, participating in sensing tasks and getting rewards can inherently risk the users' privacy and discourage their participation. In particular, the rewarding process can expose the participants' sensor data and possibly link sensitive data to their identities. In this work, we propose a privacy-preserving reward system in crowdsensing using the blind signature. The proposed scheme protects the participants' privacy by decoupling contributions and rewarding claims. Our experiment results show that the proposed mechanism is feasible and efficient.
众包感知系统已经被开发出来用于广域感知任务，因为人类携带的智能手机已经普及并变得越来越强大。为了鼓励更多的人参与感知任务，提出了各种激励机制。然而，参与感知任务并获得奖励可能会固有地危及用户的隐私，并阻碍他们的参与。特别是，奖励过程可能会暴露参与者的传感器数据，并可能将敏感数据与其身份联系起来。在这项工作中，我们使用盲签名在众包中提出了一种隐私保护的奖励系统。所提出的方案通过解耦贡献和奖励要求来保护参与者的隐私。我们的实验结果表明，所提出的机制是可行和有效的。
