A Fog-Assisted Privacy Preserving Scheme for Vehicular LBS Query

Outsourcing encrypted data to a powerful cloud is an efficient way to provide Location Based Service (LBS) in the Internet of Vehicles (IoV) while reducing the local overhead for vehicular LBS queries. However, existing schemes do not account for the numerous concurrent connections to the cloud while querying encrypted data on cloud servers. It poses huge challenges to the privacy-preserving and request efficiency of vehicle users. The purpose of this article is to identify the privacy and request efficiency concerns. Then, a Fog-Assisted Privacy Preserving (FAPP) scheme for vehicular LBS requests is proposed. By introducing the fog device to aggregate requests, the FAPP scheme solves the congestion problem of simultaneous massive requests. Additionally, while executing a vehicular LBS query, it uses R-tree and homomorphic encryption techniques to safeguard user privacy. The experimental findings demonstrate that, in comparison to other query strategies, the FAPP scheme is more efficient for vehicular LBS query and privacy preservation.