Side-Information Estimated Steganography via Dual-Path Super-Resolution Reconstruction

Abstract

Previous research has demonstrated that a spatial domain image can provide side-information to its downsampled cover image, allowing a steganographer to embed a secret message on the cover image more securely by modulating the initial distortion. Importantly, the steganographer must possess the original image with a higher resolution than the cover image. In practical scenarios, however, the steganographer typically only has the cover image in which he wishes to embed the secret message; he does not have access to the real, higher-resolution image. To improve the security of steganography, we would like to estimate the side-information from the cover image. This paper proposes a spatial domain image steganography framework of side-information estimated with polarity adjustment strategy based on dual-path super-resolution reconstruction, in which double estimated side-information can be used to modulate the initial distortion. How to estimate more realistic high-resolution images and how to develop an effective modulation strategy are the central issues of our methods. We use double super-resolution networks to reconstruct high-resolution images for estimating side-information, and then propose a simple and effective strategy to modulate the initial distortion using dual-path estimated side-information. Experiments demonstrate that the security of dual-path side-information steganography can significantly outperform that of conventional distortion techniques.