基于区块链的边缘移动群智感知声誉更新方案

移动群智感知利用移动用户的智能终端设备以低成本获取大量感知数据，而恶意用户可能上传虚假数据以获取奖励。声誉管理是一种有效的解决办法，但是基于云服务器的移动群智感知系统存在高延迟、单点故障和隐私泄露问题。针对这些问题，结合区块链和边缘计算构建基于区块链的边缘移动群智感知系统，提出一种感知数据隐私保护的声誉更新方案，采用轻量级的隐私保护方法聚合感知数据，根据数据质量和历史任务表现更新声誉。该方案可有效抵抗恶意用户、降低时延，避免单点故障和保护数据隐私。仿真实验证明了所提方案的可行性和高效性，理论分析证明了系统的安全性。

Reputation update scheme for blockchain-based edge mobile crowdsensing

Mobile crowdsensing(MCS) exploits mobile users carrying with smart devices to collect massive sensing data in a cost-satisfactory manner. However, malicious users intentionally upload false data to obtain rewards. The reputation management is an effective solution. However, the cloud-based mobile crowdsensing system has problems such as high latency, single point of failure and privacy disclosure. To solve these problems, this paper combined the blockchain with edge computing to construct a blockchain-based edge mobile crowdsensing system, and proposed a reputation updating scheme for privacy-preserving of sensing data. The scheme used a lightweight additive secret sharing technique to aggregate sensing data, and designed a reputation updating mechanism based on data quality and historical sensing task performance. The scheme could effectively resist malicious users, reduced the delay of the system, avoided the single point of failure and protected data privacy. The simulation results demonstrate the feasibility and efficiency of the proposed scheme, and the theoretical analysis illustrates the security of the proposed system.