  The pilot spoofing attack is considered as an active eavesdropping activity
launched by an adversary during the reverse channel training phase. By
transmitting the same pilot signal as the legitimate user, the pilot spoofing
attack is able to degrade the quality of legitimate transmission and, more
severely, facilitate eavesdropping. In an effort to detect the pilot spoofing
attack and minimize its damages, in this paper we propose a novel
random-training-assisted (RTA) pilot spoofing detection algorithm. In
particular, we develop a new training mechanism by adding a random training
phase after the conventional pilot training phase. By examining the difference
of the estimated legitimate channels during these two phases, the pilot
spoofing attack can be detected accurately. If no spoofing attack is detected,
we present a computationally efficient channel estimation enhancement algorithm
to further improve the channel estimation accuracy. If the existence of the
pilot spoofing attack is identified, a zero-forcing (ZF)-based secure
transmission scheme is proposed to protect the confidential information from
the active eavesdropper. Extensive simulation results demonstrate that the
proposed RTA scheme can achieve efficient pilot spoofing detection, accurate
channel estimation, and secure transmission.
