期刊
IEEE TRANSACTIONS ON MOBILE COMPUTING
卷 16, 期 4, 页码 934-949出版社
IEEE COMPUTER SOC
DOI: 10.1109/TMC.2016.2586058
关键词
Spatial crowdsourcing; differential privacy
资金
- US National Science Foundation [IIS-1320149, CNS-1461963]
- USC Integrated Media Systems Center (IMSC)
- Northrop Grumman
- Microsoft
- Oracle
- US National Science Foundation
- US National Science Foundation [IIS-1320149, CNS-1461963]
- USC Integrated Media Systems Center (IMSC)
- Northrop Grumman
- Microsoft
- Oracle
- US National Science Foundation
- Direct For Computer & Info Scie & Enginr
- Division Of Computer and Network Systems [1461963] Funding Source: National Science Foundation
Spatial Crowdsourcing (SC) is a transformative platform that engages individuals in collecting and analyzing environmental, social, and other spatio-temporal information. SC outsources spatio-temporal tasks to a set of workers, i.e., individuals with mobile devices that perform the tasks by physically traveling to specified locations. However, current solutions require the workers to disclose their locations to untrusted parties. In this paper, we introduce a framework for protecting location privacy of workers participating in SC tasks. We propose a mechanism based on differential privacy and geocasting that achieves effective SC services while offering privacy guarantees to workers. We address scenarios with both static and dynamic (i.e., moving) datasets of workers. Experimental results on real-world data show that the proposed technique protects location privacy without incurring significant performance overhead.
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