FHY-layer authentication with multiple landmarks with reduced communication overhead

In this paper, we propose a physical (PHY)-layer authentication system that exploits the channel state information of radio transmitters to detect spoofing attacks in wireless networks. By using multiple landmarks and multiple antennas in the channel estimation, this authentication system enhances the spatial resolution of the channel information and thus improves the spoofing detection accuracy. Unlike most existing hypothesis test based PHY-layer authentication schemes that rely on the known radio channel model, our proposed authentication system uses the logistic regression to remove the assumption on the known channel model and is applicable to more generic wireless networks. The Frank-Wolfe algorithm is then used to estimate the parameters of the logistic regression model, which solves the convex problem under a ℓ
₁
-norm constraint for weight sparsity to avoid over-fitting in the learning process. The distributed Frank-Wolfe algorithm can further reduce the communication overhead between the landmarks and the security agent while keeping the spoofing detection accuracy. Simulation results can validate the accuracy of the proposed PHY-layer authentication with multiple landmarks and show the performance gain regarding the overall communication overhead.