Robust image steganography framework based on generative adversarial network

Abstract

Robust steganography enables secret information to be transmitted stealthily and accurately in lossy channels such as social channels and wireless channels. With the development of deep learning, robust steganography can be constructed using the generative model of deep neural networks. Two new robust steganographic frameworks are proposed on the basis of generative models, and two algorithms are proposed on these two frameworks to verify the effectiveness of the proposed framework. Experiments show that the two frameworks proposed are more flexible than existing robust steganographic frameworks. To further verify the validity of the framework, when compared with existing robust steganography based on deep learning, the generative robust steganography algorithm is shown to have a higher secret information embedding capacity and higher steganography image quality.