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With millimeter wave (mmWave) wireless communication envisioned to be the keyenabler of next generation high data rate wireless networks, security is ofparamount importance. While conventional security measures in wireless networksoperate at a higher layer of the protocol stack, physical layer securityutilizes unique device dependent hardware features to identify and authenticatelegitimate devices. In this work, we identify that the manufacturing tolerancesin the antenna arrays used in mmWave devices contribute to a beam pattern thatis unique to each device, and to that end we propose a novel devicefingerprinting scheme based on the unique beam patterns used by the mmWavedevices. Specifically, we propose a fingerprinting scheme with multiple accesspoints (APs) to take advantage of the rich spatial-temporal information of thebeam pattern. We perform comprehensive experiments with commercialoff-the-shelf mmWave devices to validate the reliability performance of ourproposed method under various scenarios. We also compare our beam patternfeature with a conventional physical layer feature namely power spectraldensity feature (PSD). To that end, we implement PSD feature basedfingerprinting for mmWave devices. We show that the proposed multiple APsscheme is able to achieve over 99% identification accuracy for stationary LOSand NLOS scenarios and significantly outperform the PSD based method. Formobility scenarios, the overall identification accuracy is 96%. In addition, weperform security analysis of our proposed beam pattern fingerprinting systemand PSD fingerprinting system by studying the feasibility of performingimpersonation attacks. We design and implement an impersonation attackmechanism for mmWave wireless networks using state-of-the-art 60 GHz softwaredefined radios. We discuss our findings and their implications on the securityof the mmWave wireless networks.

Physical Layer Identification based on Spatial-temporal Beam Features for Millimeter Wave Wireless Networks