An Efficient Privacy Preserving Authentication with Insider Attack Resistance for VANET

By enabling automobiles to connect with one another and with roadside infrastructure, VANETs or vehicular ad hoc networks, emerged as a crucial technology to facilitate traffic management and increase road safety. However, because of their openness and dynamic nature, VANETs are vulnerable to a number of security risks, including insider attacks that take advantage of nefarious actors already present on the network. The widespread deployment of VANETs faces significant challenges concerning privacy preservation and insider attack resistance during the authentication process. Further, issues with privacy and vehicle tracing in these networks continue to be major barriers to their wider implementation. In order to overcome these issues, this study offers a novel strategy that combines Proof of Chain (PoC) and Causal Dependency mechanisms. The proposed PoC system enables secure communication, non-repudiation, and data integrity. The names and whereabouts of participating cars are also protected by privacy-enhancing measures. Contrarily, causal dependence is critical for ensuring that messages are processed in the proper order, guarding against replay attacks, and enabling vehicles to determine the applicability of received information to their current condition. These methods greatly lessen the traceability of individual cars, enabling them to exchange data, manage traffic, and convey vital safety information without compromising their privacy or security.