Abstract:

In the field of steganography, applying adversarial example technology to enhance cover image is an important method to improve the security of steganography. However, current enhancement methods of cover image based on adversarial example need to generate specific adversarial noise for each cover image independently, which leads to low efficiency and poor practicability. Furthermore, enhanced cover images have poor transfer ability against different steganalyzers. In order to solve the above-mentioned problems, this paper proposed an efficient enhancement algorithm of cover image based on universal adversarial noise. The proposed algorithm applied the adversarial example generation method DeepFool as the basic technique to construct a universal adversarial noise, which used a cyclic iterative strategy and assigned the success rate of attack on the steganalyzer as the target of optimization. Then the enhancement of cover image was achieved by adding universal adversarial noise to the cover image. For the proposed method, a single universal adversarial noise can enhance different cover images, which improves the time efficiency of cover enhancement significantly. Besides, to further improve the transfer ability of enhanced cover image, this paper fused the universal adversarial noise of different steganalyzers to obtain a fused universal adversarial noise. The use of fused universal adversarial noise can improve the security of the enhanced cover image to different steganalyzers. The experimental results show that the proposed method can achieve a significant improvement of time efficiency with other state-of-the-art algorithms. Futhermore, the cover image enhanced by the fused universal adversarial noise has much better security to different steganalyzers after embedding secret information.

Key words: information hiding, image steganography, enhancing cover image, adversarial example