A High-Performance Image Steganography Scheme Based on Dual-Adversarial Networks

This letter proposes a high-performance image steganography scheme based on dual-adversarial networks to enhance the performance of secret message hiding. According to the characteristics of generative adversarial networks, a dual-adversarial steganography scheme is devised to improve both the visual quality and the steganalysis resistance capability of the stego image. In the first adversarial block, the U-net structure is employed to reconstruct the original image as the generated image, and the adversarial noise is imperceptibly embedded into the generated image to produce the adversarial image that is most suitable for data hiding. In the second adversarial block, secret messages are undetectably embedded into the adversarial image under the confrontation of multiple steganalysis networks. Moreover, a multiple-channel attention module is introduced to enhance the performance of the adversarial image and accelerate the convergence speed of the proposed dual-adversarial networks. Additionally, the MSE loss is employed to minimize the divergence between the original and the adversarial image. Experimental results indicate that the average PSNR of the adversarial images reach 41 dB, and the detection probability is 2.79% lower than that of other advanced schemes. The proposed scheme outperforms its counterparts in terms of performance.