A coverless steganography method based on generative adversarial network
Xintao Duan, Baoxia Li, Daidou Guo, Zhen Zhang, Yuanyuan Ma
Abstract
The traditional information hiding is realized by embedding the secret information into the multimedia, but it will inevitably leave the modification mark in the carrier. This paper proposed a new method of coverless information hiding. First, the improved Wasserstein GAN (WGAN-GP) model is constructed, and the model is trained with disguised images and secret images. Then, after the model is stable, a disguised image is passed to the generator. Finally, the generator generates the image that is visually the same as the secret image, thereby achieving the same effect as transmitting the secret image. Experimental results show that this method not only has a good effect on the security of secret information transmission, but also increases the capacity of information hiding.