Scholarlink

<p>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-<i>k</i>-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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月14日

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

摘要

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.