Location Privacy Threats and Protections in 6G Vehicular Networks: A Comprehensive Review
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866912179356172288 |
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| author | Ma, Baihe Wang, Xu Lin, Xiaojie Jiang, Yanna Sun, Caijun Wang, Zhe Yu, Guangsheng Zhu, Suirui He, Ying Ni, Wei Liu, Ren Ping |
| author_facet | Ma, Baihe Wang, Xu Lin, Xiaojie Jiang, Yanna Sun, Caijun Wang, Zhe Yu, Guangsheng Zhu, Suirui He, Ying Ni, Wei Liu, Ren Ping |
| contents | Location privacy is critical in vehicular networks, where drivers' trajectories and personal information can be exposed, allowing adversaries to launch data and physical attacks that threaten drivers' safety and personal security. This survey reviews comprehensively different localization techniques, including widely used ones like sensing infrastructure-based, optical vision-based, and cellular radio-based localization, and identifies inadequately addressed location privacy concerns. We classify Location Privacy Preserving Mechanisms (LPPMs) into user-side, server-side, and user-server-interface-based, and evaluate their effectiveness. Our analysis shows that the user-server-interface-based LPPMs have received insufficient attention in the literature, despite their paramount importance in vehicular networks. Further, we examine methods for balancing data utility and privacy protection for existing LPPMs in vehicular networks and highlight emerging challenges from future upper-layer location privacy attacks, wireless technologies, and network convergences. By providing insights into the relationship between localization techniques and location privacy, and evaluating the effectiveness of different LPPMs, this survey can help inform the development of future LPPMs in vehicular networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_04503 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Location Privacy Threats and Protections in 6G Vehicular Networks: A Comprehensive Review Ma, Baihe Wang, Xu Lin, Xiaojie Jiang, Yanna Sun, Caijun Wang, Zhe Yu, Guangsheng Zhu, Suirui He, Ying Ni, Wei Liu, Ren Ping Cryptography and Security Location privacy is critical in vehicular networks, where drivers' trajectories and personal information can be exposed, allowing adversaries to launch data and physical attacks that threaten drivers' safety and personal security. This survey reviews comprehensively different localization techniques, including widely used ones like sensing infrastructure-based, optical vision-based, and cellular radio-based localization, and identifies inadequately addressed location privacy concerns. We classify Location Privacy Preserving Mechanisms (LPPMs) into user-side, server-side, and user-server-interface-based, and evaluate their effectiveness. Our analysis shows that the user-server-interface-based LPPMs have received insufficient attention in the literature, despite their paramount importance in vehicular networks. Further, we examine methods for balancing data utility and privacy protection for existing LPPMs in vehicular networks and highlight emerging challenges from future upper-layer location privacy attacks, wireless technologies, and network convergences. By providing insights into the relationship between localization techniques and location privacy, and evaluating the effectiveness of different LPPMs, this survey can help inform the development of future LPPMs in vehicular networks. |
| title | Location Privacy Threats and Protections in 6G Vehicular Networks: A Comprehensive Review |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2305.04503 |