Joint Minimax Optimization of Privacy-Preserving Authentication and Communication Overhead in Secure Vehicle-to-Edge Networks

Abstract

Internet of Vehicles (IoV) for provisioning Intelligent Transportation Systems (ITS) in Vehicular Ad Hoc Networks (VANETs) emphasized secure communication ensuring privacy-constraint of vehicle users among vehicles name as Vehicle-to-Vehicle (V2V) and among the infrastructure name as Vehicle-to-Infrastructure (V2I) communication. However, with the increase of vehicle density, congested urban roads, high-speed highway and open wireless nature, it is vulnerable to a wider range of network attacks. Existing security mechanisms in providing lightweight security mechanisms employed trust based authentication. However, these methods induce high network overhead and high latency for trust validation. This work addresses the research limitations by presenting a privacy preserving-aware authentication (PPA) algorithm with novel trust metrics, which guarantees lower latency and overhead, thus ensuring better security and improving the overall network performance requirement of ITS. The experiment is performed in complicated propagation environments, showing that PPA outperforms the baselines in terms of network performance satisfying the requirement of ITS.