A QR-Anchored Secure Offloading for Intelligent Transportation Using Planar Graph Modeling

The proliferation of connected vehicles intensifies critical challenges in computation offloading, particularly concerning security, communication stability, and scalability within Intelligent Transportation Systems (ITS). Existing offloading strategies are prone to routing loops, unstable vehicular connectivity, and are vulnerable to impersonation and Man-in-the-Middle (MitM) attacks. To address these issues, this paper proposes a novel secure offloading framework that integrates a mobility-aware planar spanner graph for robust routing and a lightweight QR-code-based protocol for decentralized authentication. The graph theoretic component dynamically constructs a stable network topology that eliminates routing loops and provides proven bounded-path stretch which ensure routing optimality under dynamic urban mobility conditions. The QR-anchored mechanism establishes an initial trust between vehicles and Roadside Units (RSUs) through a visual channel which mitigate impersonation attacks without the overhead of traditional Public Key Infrastructure (PKI). Performance of the proposed method is evaluated through extensive simulations on the Veins-OMNeT++/SUMO platform under a dense urban grid scenario. The results demonstrate that our solution significantly outperforms state-of-the-art baselines like Multi-Layer Task Offloading (MTO), Mx-TORU, and Delay-Sensitive Task Offloading (MAFCPTORA), achieve up to 19% lower latency, a 22% higher task success ratio, and 17% reduced computational overhead on resource-constrained On-Board Unit (OBUs). This work highlights the efficacy of combining graph-theoretic routing with lightweight cryptography to enhance the security and efficiency of ITS offloading platforms.