Coverless Information Hiding Based on Generative adversarial networks

Understand

Traditional image steganography modifies the content of the image more or less, it is hard to resist the detection of image steganalysis tools.

• To address this problem, a novel method named generative coverless information hiding method based on generative adversarial networks is proposed in this paper.
• The main idea of the method is that the class label of generative adversarial networks is replaced with the secret information as a driver to generate hidden image directly, and then extract the secret information from the hidden image through the discriminator.
• It's the first time that the coverless information hiding is achieved by generative adversarial networks.