A Dual Mode Privacy-Preserving Scheme Enabled Secure and Anonymous for Edge Computing Assisted Internet of Vehicle Networks

This paper adopts Named Data Network technology for data delivery/forwarding over the Internet of Vehicles (IoVs) and proposes an NDN-based architecture for IoVs based on mobile edge computing(MEC). Advanced research has demonstrated the considerable benefits of introducing MEC into IoVs, but comes with issues such as insufficient security and privacy protection problems. To address these issues, we propose a dual-mode privacy-preserving framework for the security layer of the proposed network architecture. Specifically, we construct a privacy protection identity-based broadcast proxy re-encryption scheme to provide privacy to a set of vehicles with data requests. Furthermore, we use a federated learning scheme based on local differential privacy in the proposed NDN-based architecture for MEC-empowered IoV to achieve high-speed response and decision making. Simulation results demonstrate that our proposed scheme performs effectively.