  With millimeter wave (mmWave) wireless communication envisioned to be the key
enabler of next generation high data rate wireless networks, security is of
paramount importance. While conventional security measures in wireless networks
operate at a higher layer of the protocol stack, physical layer security
utilizes unique device dependent hardware features to identify and authenticate
legitimate devices. In this work, we identify that the manufacturing tolerances
in the antenna arrays used in mmWave devices contribute to a beam pattern that
is unique to each device, and to that end we propose a novel device
fingerprinting scheme based on the unique beam patterns used by the mmWave
devices. Specifically, we propose a fingerprinting scheme with multiple access
points (APs) to take advantage of the rich spatial-temporal information of the
beam pattern. We perform comprehensive experiments with commercial
off-the-shelf mmWave devices to validate the reliability performance of our
proposed method under various scenarios. We also compare our beam pattern
feature with a conventional physical layer feature namely power spectral
density feature (PSD). To that end, we implement PSD feature based
fingerprinting for mmWave devices. We show that the proposed multiple APs
scheme is able to achieve over 99% identification accuracy for stationary LOS
and NLOS scenarios and significantly outperform the PSD based method. For
mobility scenarios, the overall identification accuracy is 96%. In addition, we
perform security analysis of our proposed beam pattern fingerprinting system
and PSD fingerprinting system by studying the feasibility of performing
impersonation attacks. We design and implement an impersonation attack
mechanism for mmWave wireless networks using state-of-the-art 60 GHz software
defined radios. We discuss our findings and their implications on the security
of the mmWave wireless networks.
