Physical layer eavesdropping detection technology based on machine learning in large-scale MIMO system

The security of physical layer is very important in wireless communication.Effective physical layer security mechanism can provide effective security mechanism for wireless communication and reduce system complexity for later secure communication.This paper proposes an active eavesdropping user detection method based on k-means clustering analysis technology.This method does not need to design pilot sequences and estimate legitimate user channel statistics.The required clustering information is obtained by constructing a sequence with only legitimate user information, and then eavesdropping detection is performed on the signals received by the base station.Simulation results show that compared with the traditional eavesdropping detection scheme, the machine learning-based method proposed in this paper has a significant improvement in performance.