Physical Layer Secret Key Generation for Spatially Correlated Channels Based on Multi-Task Autoencoder

Physics layer key, as an emerging method to enhance information security, is generated based on the reciprocity and spatial decorrelation of wireless channels. However, due to the half-duplex mode of the communication systems, the channels detected by the legitimate sides are not completely reciprocal. Meanwhile, when the eavesdropper is extremely close to the legitimate side, the spatial correlation could be very strong and threaten the information security. This paper combines the autoencoder and the multi-task learning into a novel physical layer key generation scheme, i.e., Multi-Task Autoencoder (MTAE). MTAE extracts the reciprocal features from the weakly correlated channel estimates of the legitimate sides while reducing its correlation with eavesdropper. Simulation results show good randomness and consistency with the primary keys generated based on MTAE for the legitimate sides, while increasing the difference in the extracted features between eavesdropper and its adjacent node. The proposed method has great potential in scenarios requiring high security.