Full Program
Summary:
Cellular Vehicle-to-Everything (C-V2X) communication underpins intelligent transportation systems but remains susceptible to spoofing attacks that inject false information, compromising safety and reliability. While traditional cryptographic security verifies sender credentials, it cannot assure the veracity of message content if credentials are compromised. Physical Layer Security (PLS) provides a complementary defense by analyzing inherent wireless signal characteristics. This paper details the implementation and simulation of an SDR-DL (Software-Defined Radio and Deep Learning) framework for C-V2X spoofing detection, inspired by recent research. The Python-based simulation, utilizing TensorFlow/Keras for the PCD and PyTorch Geometric for the GNN, demonstrates the framework's feasibility, achieving high detection accuracy for the modeled spoofing scenarios based on RSSI patterns. We discuss implementation details, highlight challenges including data requirements and computational complexity, and propose future research directions such as multi-feature fusion and explainable AI integration.Author(s):
Danilo Greco
Italy
Muhammad Saad Sohail
Pakistan