Detection and Identification of Spoofed Pilots in TDD/SDMA Systems

In a time-division duplex (TDD) multiple antenna system, the channel state information can be estimated using reverse training. A pilot spoofing attack occurs when during the training phase, an adversary (spoofer) also sends identical training (pilot) signal as that of the legitimate receiver. This contaminates channel estimation and alters the legitimate precoder design, facilitating eavesdropping. A recent approach proposed superimposing a random sequence on the training sequence at the legitimate receivers, and then using the minimum description length (MDL) criterion to detect pilot spoofing attack via source enumeration. In this letter, we extend this approach by exploiting temporal subspace properties of the pilot signals in conjunction with the MDL criterion, to determine which pilots are contaminated by a spoofer, and which ones are free of spoofing attack. The identification performance is illustrated via simulations.