LPPS-IKHC: Location Privacy-Preserving Scheme Using Improved $k$-Anonymity and Hybrid Cache for IoV
Yufeng Li, Bo Wang, Qi Liu, Xiangyu Zheng, Jiangtao Li, Yiwei Wang, Jiade Xi, Wutao Qin · IEEE Transactions on Vehicular Technology · 2025
As the Internet of Vehicles (IoV) evolves, integrating Location-Based Services (LBS) into in-vehicle software has become increasingly common. Consequently, protecting users' location privacy has emerged as a critical concern. Vehicles face the challenge of sending query requests to untrusted Location Service Providers (LSP) through untrusted Roadside Units (RSU) to obtain relevant results. This situation presents two primary risks: 1) the involvement of untrusted RSU increases the likelihood of monitoring vehicle communications with the LSP, and 2) repeated queries to the untrusted LSP increase the risk of privacy breaches during interactions. This paper proposes an innovative location privacy protection scheme for continuous LBS in the IoV, called LPPS-IKHC, which combines improved$k$-anonymity with hybrid cache. The scheme utilizes anonymous techniques and hybrid cache to mitigate the risk of exposing sensitive information to untrusted entities. To protect against adversaries, LPPS-IKHC generates specific anonymous sets in the presence of untrusted RSU. Additionally, an anonymous algorithm incorporating trajectory similarity is introduced to protect trajectory privacy, further enhancing user location privacy. Furthermore, by reducing the number of interactions between vehicles and untrusted LSP, hybrid caching helps diminish the risk of privacy disclosure. Extensive experimental results demonstrate that the LPPS-IKHC method provides superior privacy protection and lower system overhead compared to existing schemes.