Detecting Location Spoofing Attacks using Multiple Angle of Signal Arrivals in MM-Wave Vehicular Networks

Millimeter-wave (mm-wave) vehicular communication networks are expected to revolutionize intelligent transportation systems by enabling ultra-reliable, low-latency, and high-speed data exchange. A major challenge that needs to be addressed in these networks is the presence of malicious user activity that can disrupt the network through various means. These malicious activities include manipulating safety messages or launching location spoofing attacks. To tackle this challenge, a physical-layer-based location spoofing attack detection technique for mm-wave vehicular networks is proposed in this paper. The proposed technique makes use of the additional channel measurements available in systems with hybrid antenna architectures to enable joint beamforming and channel sensing. Spoofing attack detection is achieved by verifying a cluster of estimated angles of arrivals with the reported location information. The numerical results show that the proposed technique is highly accurate in detecting location spoofing attacks using just a few communication packets at the receiver without the need for a dedicated channel sensing stage or extra communication overhead.