CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography

TL;DR

CRoSS leverages diffusion models, specifically Stable Diffusion, to enhance controllability, robustness, and security in image steganography without additional training, marking a novel application in the field.

Contribution

This work introduces the first use of diffusion models in image steganography, improving security and robustness while maintaining controllability without extra training.

Findings

CRoSS outperforms traditional methods in controllability and security.

The framework demonstrates high robustness against image degradation.

No additional training required for the diffusion-based steganography.

Abstract

Current image steganography techniques are mainly focused on cover-based methods, which commonly have the risk of leaking secret images and poor robustness against degraded container images. Inspired by recent developments in diffusion models, we discovered that two properties of diffusion models, the ability to achieve translation between two images without training, and robustness to noisy data, can be used to improve security and natural robustness in image steganography tasks. For the choice of diffusion model, we selected Stable Diffusion, a type of conditional diffusion model, and fully utilized the latest tools from open-source communities, such as LoRAs and ControlNets, to improve the controllability and diversity of container images. In summary, we propose a novel image steganography framework, named Controllable, Robust and Secure Image Steganography (CRoSS), which has significant advantages in controllability, robustness, and security compared to cover-based image steganography methods. These benefits are obtained without additional training. To our knowledge, this is the first work to introduce diffusion models to the field of image steganography. In the experimental section, we conducted detailed experiments to demonstrate the advantages of our proposed CRoSS framework in controllability, robustness, and security.