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Association for Computing Machinery (ACM), ACM Computing Surveys, 1(54), p. 1-36, 2021

DOI: 10.1145/3423165

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Location Privacy-preserving Mechanisms in Location-based Services

Journal article published in 2021 by Hongbo Jiang ORCID, Jie Li, Ping Zhao, Fanzi Zeng ORCID, Zhu Xiao ORCID, Arun Iyengar
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Location-based services (LBSs) provide enhanced functionality and convenience of ubiquitous computing, but they open up new vulnerabilities that can be utilized to violate the users’ privacy. The leakage of private location data in the LBS context has drawn significant attention from academics and industry due to its importance, leading to numerous research efforts aiming to confront the related challenges. However, to the best of our knowledge, none of relevant studies have performed a qualitative and quantitative comparison and analysis of the complex topic of designing countermeasures and discussed the viability of their use with different kinds of services and the potential elements that could be deployed to meet new challenges. Accordingly, the purpose of this survey is to examine the privacy-preserving techniques in LBSs. We categorize and provide an inside-out review of the existing techniques. Performing a retrospective analysis of several typical studies in each category, we summarize their basic principles and recent advances. Additionally, we highlight the use of privacy-preserving techniques in LBSs for enabling new research opportunities. Providing an up-to-date and comprehensive overview of existing studies, this survey may further stimulate new research efforts into this promising field.