Toward location privacy protection in Spatial crowdsourcing

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ID: 90012
2019
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Abstract
Spatial crowdsourcing is an emerging outsourcing platform that allocates spatio-temporal tasks to a set of workers. Then, the worker moves to the specified locations to perform the tasks. However, it usually demands workers to upload their location information to the spatial crowdsourcing server, which unavoidably attracts attention to the privacy-preserving of the workers’ locations. In this article, we propose a novel framework that can protect the location privacy of the workers and the requesters when assigning tasks to workers. Our scheme is based on mathematical transformation to the location while providing privacy protection to workers and requesters. Moreover, to further preserve the relative location between workers, we generate a certain amount of noise to interfere the spatial crowdsourcing server. Experimental results on real-world data sets show the effectiveness and efficiency of our proposed framework.
Reference Key
ye2019towardinternational Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ye, Hang;Han, Kai;Xu, Chaoting;Xu, Jingxin;Gui, Fei;
Journal international journal of distributed sensor networks
Year 2019
DOI
DOI not found
URL
https://doi.org/10.1177/1550147719830568
Keywords
Medicine Technology (General) Information technology Technology Science (General) Science mathematics electronic computers. computer science philosophy. psychology. religion ethics

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