Dynamic-anonymous privacy-preserving authenticated aggregation for safety-warning system for the Internet of Vehicles

Abstract

Currently, the connectivity of vehicles using the latest communication and computing technologies has grown as the Internet of Vehicles (IoV). IoV has been utilized to foster an easy traffic flow by sharing safety-warning messages. However, authentication and confidentiality of shared information is a challenging issue. To solve the problem, various privacy-preserving authenticated data-aggregation schemes have been devised. However, existing schemes have shortcomings specifically concerning a heavy computational cost, and the need for a secure channel. Besides, static pseudonyms may increase the risk of a vehicle’s privacy leakage. In response to these challenges, this study introduces a new pairing-less and secure privacy-preserving authenticated data aggregation (PLS-PPADA) scheme. Leveraging the pairing-less and certificate-based setting, the PLS-PPADA scheme emerges as a robust, efficient, and effective solution for safety-warning systems in IoV. Further, to resolve the risk of privacy leakage due to static pseudonyms, the paradigm of fuzzy identity has been utilized. Thus, it achieves efficiency and dynamic anonymity and also does not require a secure channel for key sharing. A comprehensive security analysis underscores its effective data protection capabilities and efficiency comparison presents it as a compelling alternative to existing state-of-the-art schemes.