Verifiable and privacy-preserving fine-grained data management in vehicular fog computing: A game theory-based approach

Vehicular fog computing (VFC) is a powerful technology that extends fog computing to regular vehicular networks, providing end-users and vehicles with ultra-low-latency services. It enables connected Vehicular Fog Nodes (VFNs) to process real-time data and promptly respond to user queries. However, touching unencrypted data by VFNs raises security challenges definitely, the top of which is confidentiality, and giving encrypted data to VFNs causes other problems such as encrypted data processing. Apart from these, how to inspect and encourage VFNs to provide a secure, honest, and user-satisfactory network is of vital importance to this area. To address these challenges, we design a novel fine-grained data management (FGDM) approach for VFC-assisted systems. Our FGDM provides control over both retrieval and access to outsourced data in fine-grained ways. Also, it offers highly efficient approaches for the accuracy verification of operations performed by VFNs. In designing the system, we consider a three-player game among system entities to capture their interactions. We formulate the management problems as a Nash Equilibrium (NE) problem and show the existence of an equilibrium. Our security analysis and empirical results demonstrate that the FGDM is secure in the standard model and acceptably efficient. Our scheme's performance is rigorously assessed, offers improved speed, and is cost-effective compared to existing methods. It reduces computational and communication costs, achieving a reduction of nearly 25% compared to comparable designs.