Towards Privacy-Preserving Task Assignment for Fully Distributed Spatial Crowdsourcing
We propose a spatial crowdsourcing task assignment system that can protect users’ location privacy in a fully distributed scenario. We leverage homomorphic encryption to protect the location information of workers and task requesters. We propose a “wait-and-decide” and a “proportional-backoff” mechanism to improve the quality of task assignment in such a fully distributed scenario.