A novel location privacy preserving scheme for spatial crowdsourcing
Bin Zhu, Shuai Zhu, Xuejie Liu, Yuanhong Zhong, Hua Bing Wu · 2016
In order to avoid disclosing the location privacy of the workers to the requester and the server in spatial crowdsourcing, we propose a novel location privacy preserving scheme. In the scheme, the registered online workers execute the distributed spatial clustering algorithm and the coordinate of each virtual cluster center is reported to the server by each cluster head. Base on the proposed clustering algorithm, we introduce a two-level spatial task assignment algorithm which includes the primary assignment phase and secondary assignment phase executed by the server and the cluster head, respectively. The simulation results indicate that the proposed scheme can effectively accomplish the spatial task assignment without compromising the location privacy of the workers.