PrivGeoCrowd: A toolbox for studying private spatial Crowdsourcing

Abstract

Spatial Crowdsourcing (SC) is a novel and transformative platform that engages individuals, groups and communities in the act of collecting, analyzing, and disseminating environmental, social and other spatio-temporal information. SC outsources a set of spatio-temporal tasks to a set of workers, i.e., individuals with mobile devices that perform the tasks by physically traveling to specified locations of interest. Protecting location privacy is an important concern in SC, as an adversary with access to individual whereabouts can infer sensitive details about a person (e.g., health status, political views). Due to the challenging nature of protecting worker privacy in SC, solutions for this problem are quite complex, and require tuning of several parameters to obtain satisfactory results. In this paper, we propose PrivGeoCrowd, a toolbox for interactive visualization and tuning of SC private task assignment methods. This toolbox is useful for several real-world entities that are involved in SC, such as: mobile phone operators that want to sanitize datasets with worker locations, spatial task requesters, and SC-service providers that match workers to tasks.