A scoping review of privacy protection in LBS: Architectures, Threats, and Defense mechanisms

Yuxi Li, Jingjing Chen, Dong Ji, Fa Zhu, Xingchi Chen, Huilai Zhi, Daxin Zhu, Athanasios V. Vasilakos

Abstract: Location-based services (LBS) generate large volumes of spatiotemporal data, raising significant privacy concerns. Yet the field lacks a systematic survey that examines security risks across the full LBS data lifecycle and provides a comprehensive comparison of privacy-preserving mechanisms. This scoping review advances LBS privacy by offering a lifecycle-aware synthesis, a rigorous comparative framework, and a forward-looking agenda for research and deployment. Specifically, we: (1) map attack surfaces and quantify privacy–utility trade-offs across collection, storage, transmission, processing, and sharing, with particular attention to server-side threats and untrusted providers; (2) develop a multidimensional framework that compares leading techniques-k-anonymity, differential privacy, perturbation/obfuscation, and encrypted search-in terms of protection strength, computational/communication overhead, and deployment suitability; and (3) identify technical bottlenecks and outline research directions aligned with emerging scenarios and industry trends. Together, these contributions provide actionable criteria for selecting, combining, and deploying robust, efficient LBS privacy solutions.

External IDs:dblp:journals/jksucis/LiCJZCZZV25