SAVE: Efficient Privacy-Preserving Location-Based Service Bundle Authentication in Self-Organizing Vehicular Social Networks.

Self-organizing vehicular social networks underpin many location-based services (LBS) such as those that collect and share environmental information (e.g., traffic and weather conditions) among vehicular users and the infrastructure. There are, however, security and privacy considerations in the sharing of such information, and one popular approach is to design lightweight authentication solutions for LBS. Existing approaches may suffer from limitations such as significant computational and/or storage overheads, latency and time delays, and consequently impractical for resource-constrained on-board units. In this paper, we propose an efficient privacy-preserving LBS bundle authentication scheme (hereafter referred to as SAVE) through secure redundancy filtering in self-organizing vehicular social networks. Firstly, an enhanced self-healing key distribution protocol with distributed revocation is proposed to reduce communication cost for retransmitting lost key material and resist free-riding attacks to enhance the authentication efficiency. Then, based on it, a generalized version of online/offline aggregate signature is proposed to achieve batch LBS bundle verification based on arbitrary one-way function holding the property of multiplicative homomorphism. Finally, an efficient zero-knowledge range proof based on lightweight one-way hash chain is designed to decide the redundancy of LBS bundles without disclosing vehicular users’ location privacy. Formal security proof and extensive simulation results demonstrate that our proposed SAVE achieves identity privacy, two levels of location privacy and the practicability in reality. [ABSTRACT FROM AUTHOR]