Model-Driven Learning-Based Physical Layer Authentication for Mobile Wi-Fi Devices

This research addresses authentication risks in wireless IoT devices by proposing LiteNP-Net, a lightweight neural network for physical layer authentication (PLA, a security method that verifies device identity using unique wireless channel characteristics). The approach combines hypothesis testing theory with deep learning to create a system that works effectively even without detailed prior knowledge of wireless channel properties, and testing showed it performs better than existing methods in real-world Wi-Fi environments.