Secure RIS-Aided MISO-NOMA System Design in the Presence of Active Eavesdropping

Abstract

As for the time-division communications system, the pilot spoofing attack (PSA) technique is maliciously utilized by active eavesdroppers during the uplink training phase, for contaminating the legitimate channel estimation and thus altering the beamforming design towards the eavesdroppers. Nonorthogonal multiple access (NOMA) has been recognized as the key technology for the envisioned Internet of Things (IoT) networks. In order to prevent the aforementioned information leakage in NOMA-IoT systems, we develop a novel two-way training scheme to detect PSA and a robust secure beamforming design for providing secure transmission, by utilizing the emerging technique of reconfigurable intelligent surface (RIS), which is turned off during the uplink training phase and turned on during the downlink training phase, respectively. Considering that the perfect channel state information related to the eavesdropping channel is typically difficult to obtain, a secrecy outage probability-constrained robust secure beamforming design is proposed to maximize the achievable sum secrecy rate of the legitimate users, by alternatively optimizing the active beamforming and RIS passive beamforming, while satisfying the requirements of the NOMA transmission. Elaborate simulation results reveal that the proposed detection method attains a super PSA detection performance and the proposed robust secure beamforming design is capable of efficiently enhancing the achievable sum secrecy rate, compared with various benchmark schemes.