The Devil in the Stego Image: Far from Being Usable in Real-World Scenarios

Huanqi Wu, Huangbiao Xu, Xiao Ke

Abstract: Digital images, serving as the primary carrier of information, have been wildly spread on the Internet. Image steganography is a technology that employs images as the carrier for information hiding. While current deep image steganography demonstrated impressive encoding abilities across various media, two serious problems have been overlooked in deep image-to-image steganography and hinder its application under real-world scenarios, which we define as the problem of Pixel Value Overflow and Gap of Precision. In this paper, we explore the cause of those problems and introduce a plug-and-play Universal Suppressor to solve the application problems of deep image-to-image steganography in real-world scenarios, which can be flexibly applied to various models with different structures. Experiments demonstrate that our Universal Suppressor performs well in existing state-of-the-art (SOTA) models and confers them with intrinsic robustness for real-world deployment. The code will be released at https://github.com/aoli-gei/USP.

External IDs:doi:10.1145/3746027.3754767