Improving Robustness of TCM-based Robust Steganography with Variable Robustness

TL;DR

This paper introduces a dynamic robustness cost in steganography that improves the resilience of JPEG images against recompression, ensuring message integrity while maintaining security.

Contribution

It proposes a novel robustness cost calculation that adapts during embedding, enhancing robustness against recompression without compromising security.

Findings

Significantly improved robustness of stego images against recompression.

High accuracy in message extraction after recompression.

Effective balance between robustness and security achieved.

Abstract

Recent study has found out that after multiple times of recompression, the DCT coefficients of JPEG image can form an embedding domain that is robust to recompression, which is called transport channel matching (TCM) method. Because the cost function of the adaptive steganography does not consider the impact of modification on the robustness, the modified DCT coefficients of the stego image after TCM will change after recompression. To reduce the number of changed coefficients after recompression, this paper proposes a robust steganography algorithm which dynamically updates the robustness cost of every DCT coefficient. The robustness cost proposed is calculated by testing whether the modified DCT coefficient can resist recompression in every step of STC embedding process. By adding robustness cost to the distortion cost and using the framework of STC embedding algorithm to embed the message, the stego images have good performance both in robustness and security. The experimental results show that the proposed algorithm can significantly enhance the robustness of stego images, and the embedded messages could be extracted correctly at almost all cases when recompressing with a lower quality factor and recompression process is known to the user of proposed algorithm.