移动群智感知中基于网格混淆的位置隐私保护

针对现有移动群智感知(mobile crowd sensing, MCS)面临的隐私泄露问题,引入一种混合式区块链架构来构建系统,实现MCS的去中心化,并通过私有区块链保护工人隐私记录。采用无证书签密实现用户数据传输过程中的机密性和完整性,保证用户信息的安全性。为了降低位置隐私暴露的风险,提出一种基于网格混淆的位置隐私保护方案(location privacy protection scheme based on grid obfuscation,LPPSGO)。该方案通过H3索引系统划分多精度六边形网格,实现工人位置的空间隐匿,工人可以根据个性化隐私需求扰动自身位置,无须担心真实位置的暴露。仿真实验结果表明,LPPSGO能有效提高MCS系统的任务分配成功率,减少时间开销,与其他位置保护方案相比,安全性更强,覆盖性能更好。

Location privacy protection based on grid obfuscation in mobile crowd sensing

Aiming at the problem of privacy leakage faced by existing mobile crowd sensing (MCS), a hybrid blockchain architecture is introduced to build the system, which realizes the decentralization of MCS and protects workers’ privacy records through private blockchain. Certificateless signcryption is used to protect the confidentiality and integrity of user data transmission and ensure the security of user information. In order to reduce the risk of location privacy exposure, a location privacy protection scheme based on grid obfuscation (LPPSGO) is proposed. The scheme divides multi-precision hexagonal grids through H3 index system to realize the spatial concealment of workers’ positions. Workers can disturb their positions according to personalized privacy requirements without worrying about the exposure of real positions. Simulation results show that LPPSGO can effectively improve the task allocation success rate of MCS system and reduce the time overhead. Compared with other location protection schemes, it is more secure and has better coverage performance.