Pilot Contamination Attack Detection using Random Symbols for Massive MIMO Systems

The massive multiple-input multiple-output (MIMO) technique is recognized as the corner stone of the next generation mobile communication systems. However, its uplink-training downlink-transmission mechanism contains a severe security breach. If the uplink training sequence is artificially contaminated by some active attackers, the downlink beamforming can significantly deviate from the legitimate user and could be focused on the eavesdropper's location. This active pilot contamination attack (PCA) not only blocks the legitimate communication, but yields user information leakage. In this work, a random symbol based PCA detection method is proposed. The "secure region" is derived theoretically according to the statistical distribution of the detection statistics, which enables a more accurate PCA detection. The energy examination mechanism is also used to force the attacker sending the random symbols and exposing itself in the random symbol based attack detection. Finally, the theoretical analysis and simulation results demonstrate the superior performance of the proposed method.