Location Privacy Challenges in Spatial Crowdsourcing

Abstract

Spatial crowdsourcing has appealed attention in collecting and processing social, environmental, and other spatio-temporal data by the contribution of individuals, communities and groups of workers in the physical world. The objective of spatial crowdsourcing is to outsource a set of spatio-temporal tasks to a set of workers, which requires the workers to be physically traveling to the tasks' locations in order to perform them, i.e., taking photos or collecting real time weather information at prespecified location. However, the crowd workers privacy could be compromised by disclosing their locations to untrusted parties. This paper aims to provide a brief description of spatial crowdsourcing and highlight its privacy concerns. Thereafter, it demonstrates the common attacks in the location privacy of spatial crowdsourcing.