A Triple Real-Time Trajectory Privacy Protection Mechanism Based on Edge Computing and Blockchain in Mobile Crowdsourcing

【Author】 Wang, Weilong; Wang, Yingjie; Duan, Peiyong; Liu, Tianen; Tong, Xiangrong; Cai, Zhipeng

【Source】IEEE TRANSACTIONS ON MOBILE COMPUTING

【影响因子】6.075

【Abstract】With the rapid development of the Internet of Things (IoT) and the rapid popularization of 5 G networks, the data that needs to be processed in Mobile Crowdsourcing (MCS) system is increasing every day. Traditional cloud computing can no longer meet the needs of crowdsourcing for real-time data and processing efficiency, thus, edge computing was born. Edge computing can be calculated at the edge of network so that greatly improve the efficiency and real-time performance of data processing. In addition, most of the existing privacy protection technologies are based on the trusted third parties. Therefore, in view of the semi-trustworthiness of edge servers and the transparency of blockchain, this paper proposes a triple real-time trajectory privacy protection mechanism (T-LGEB) based on edge computing and blockchain. Through combining the localized differential privacy and multiple probability extension mechanism, the T-LGEB mechanism is proposed to send the requests and data to the edge server in this paper. Then, through the spatiotemporal dynamic pseudonym mechanism proposed in the paper, the entire trajectory of task participants is divided into multiple unrelated trajectory segments with different pseudonymous identities in order to protect the trajectory privacy of task participants while ensuring high data availability and real-time data. Through a large number of experiments and comparative analysis on multiple real data sets, the proposed T-LGEB has extremely high privacy protection capabilities and data availability, and the resource consumption caused is relatively low.

【Keywords】Blockchain; edge computing; localized differential privacy; mobile crowdsourcing; trajectory privacy

【发表时间】2023 OCT 1

【收录时间】2023-09-29

【文献类型】实验仿真

【主题类别】

区块链技术-协同技术-边缘计算