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InfoResearchPeer-reviewed
Model-Driven Learning-Based Physical Layer Authentication for Mobile Wi-Fi Devices
- Published
- Record updated
Summary
Researchers propose a learning-based physical layer authentication scheme for IoT devices over Wi-Fi, combining hypothesis testing with deep learning. They derive a Neyman-Pearson detector using conditional statistical models and build LiteNP-Net, a lightweight network that approaches that detector's performance without prior channel statistics. In Wi-Fi IoT testbed experiments, LiteNP-Net outperformed a conventional correlation-based method and state-of-the-art Siamese-based methods.