LAUSR

In a time-division duplex multiple antenna system, the channel state information can be estimated using reverse training. A pilot spoofing (contamination) attack occurs when during the training phase, an adversary (spoofer) also sends synchronized, identical training (pilot) signal as that of the legitimate receiver. This contaminates channel estimation and alters the legitimate beamforming/precoder design, facilitating eavesdropping. A recent approach proposed superimposing a random sequence on the training sequence at the legitimate receiver and then using the minimum description length (MDL) criterion to detect pilot contamination attack. In this paper, we augment this approach with estimation of both legitimate receiver and eavesdropper channels, and secure beamforming, to mitigate the effects of pilot spoofing. We consider two cases: 1) the spoofer transmits only the pilot signal and 2) the spoofer also adds a random sequence to its pilot, mimicking the legitimate receiver. We also employ a random matrix theory-based source enumeration approach instead of MDL, for spoofing detection, leading to improved detection performance. The proposed detection and mitigation approaches are illustrated via simulations.