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PrivGeoCrowd: A toolbox for studying private spatial Crowdsourcing

机译:privgeocrocd:用于学习私人空间众包的工具箱

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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.
机译:空间众包(SC)是一种新颖且变革的平台,可以参与收集,分析和传播环境,社会和其他时空信息的行为中的个人,团体和社区。 SC向一组工人提供一组时空任务,即使用移动设备的个人,通过物理地前往特定的感兴趣的位置来执行任务。保护地点隐私是SC中的一个重要问题,作为对个人的访问权,可以推断有关人员的敏感细节(例如,健康状况,政治观点)。由于保护工人隐私在SC中的挑战性质,解决问题的解决方案非常复杂,需要调整几个参数以获得满意的结果。在本文中,我们提出了PrivGeocrocd,一个工具箱,用于交互式可视化和调整SC私有任务分配方法。此工具箱对于涉及SC的几个实际实体非常有用,例如:希望与工作人员,空间任务请求者和SC-Service提供程序一起消毒数据集的移动电话运营商,这些服务提供者将工人与任务匹配。

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