Robust adaptive steganography based on dither modulation and modification with re-compression
This work addresses the challenge of secure covert communication over lossy networks for users needing reliable message extraction, representing an incremental improvement over existing robust steganography methods.
The paper tackles the problem of robust adaptive steganography for covert communication in lossy channels like JPEG compression, proposing a method that improves robustness and security, with experiments showing strong robustness and greatly enhanced security compared to prior schemes when the channel quality factor is known.
Traditional adaptive steganography is a technique used for covert communication with high security, but it is invalid in the case of stego images are sent to legal receivers over networks which is lossy, such as JPEG compression of channels. To deal with such problem, robust adaptive steganography is proposed to enable the receiver to extract secret messages from the damaged stego images. Previous works utilize reverse engineering and compression-resistant domain constructing to implement robust adaptive steganography. In this paper, we adopt modification with re-compression scheme to improve the robustness of stego sequences in stego images. To balance security and robustness, we move the embedding domain to the low frequency region of DCT (Discrete Cosine Transform) coefficients to improve the security of robust adaptive steganography. In addition, we add additional check codes to further reduce the average extraction error rate based on the framework of E-DMAS (Enhancing Dither Modulation based robust Adaptive Steganography). Compared with GMAS (Generalized dither Modulation based robust Adaptive Steganography) and E-DMAS, experiment results show that our scheme can achieve strong robustness and improve the security of robust adaptive steganography greatly when the channel quality factor is known.