Secure and Deduplicated Spatial Crowdsourcing: A Fog-Based Approach

Abstract

With the proliferation of mobile devices, spatial crowdsourcing is rising as a new paradigm that enables individuals to participate in tasks related to some locations in the physical world. Nevertheless, how to allocate these tasks to proper mobile users and improve communication efficiency are critical in spatial crowdsourcing. In this paper, we propose Fo-DSC, a fog-based deduplicated spatial crowdsourcing framework to achieve precise task allocation and secure data deduplication. Specifically, by integrating fog computing, we design a two-step task allocation mechanism to improve the accuracy of tasks allocation in spatial crowdsourcing. The fog nodes can detect and erase the repeated data in crowdsensing reports without learning any information about the reports. Furthermore, Fo-DSC efficiently records the contributions of mobile users whose data are reduplicated and deleted. As a result, these users do not become discouraged. Finally, we demonstrate that Fo-DSC satisfies the properties of fog-based task allocation and secure data deduplication with low computational and communication overheads.