New LLRT-Based Methods for Active Eavesdropper Detection in Cell-Free Massive MIMO

In this paper, the problem of active eavesdropper detection is considered for a cell-free massive multiple-input multiple-output (m-MIMO) system which is attacked by an active eavesdropper within the uplink training phase, also called pilot spoofing attack. Two methods based on log-likelihoodratio tests (LLRT), one in a centralized and the other in a decentralized fashion, are proposed to detect the signal abnormality. The methods take advantage of a special protocol in which the legitimate users switch to an off-mode irregularly, without significantly affecting the spectral efficiency of the data transmission. The protocol is directly applicable to environments with low to moderate mobility, and can be extended to high mobility through a simple rearrangement of available pilot sequences among users if needed. More importantly, the proposed methods impose low fronthaul overhead which is imperative for a cellfree m-MIMO system with a large number of access points (APs). A closed-form expression for the joint probability density function (PDF) of the processed received signals conditioned on the alternative hypothesis, which is essential for the implementation of LLRT-based detection methods, is also derived. Through an asymptotic analysis, it is shown for the proposed methods that the detection and false-alarm probabilities approach to one and zero, respectively as the number of APs goes to infinity. Numerical results reveal that both methods significantly outperform a recent approach in terms of false-alarm rate with negligible degradation in the per user uplink spectral efficiency.