New Design Paradigm of Distortion Cost Function for Efficient JPEG Steganography
This addresses the problem of secure data hiding in JPEG images for steganography practitioners, offering an incremental improvement over existing methods.
The paper tackles the challenge of designing JPEG steganographic distortion cost functions to resist JPEG phase-aware steganalysis features like GFR, by introducing a Distortion Cost Domain Transformation (DCDT) function that optimizes embedding in the decompressed spatial domain. Experimental results show DCDT with HiLL outperforms state-of-the-art schemes like UERD and J-UNIWARD in resisting detection by GFR and SCA-GFR, and rivals BET-HiLL with 10x lower computational complexity.
Recently, with the introduction of JPEG phase-aware steganalysis features, e.g., GFR, the design of JPEG steganographic distortion cost function turns to maintain not only the statistical undetectability in DCT domain but also in spatial domain. To tackle this issue, this paper presents a novel paradigm for the design of JPEG steganographic distortion cost function, which calculates the distortion cost via a generalized Distortion Cost Domain Transformation (DCDT) function. The proposed function comprises the decompressed pixel block embedding changes and their corresponding embedding distortion costs for unit change, where the pixel embedding distortion costs are represented in a more general exponential model, aiming to flexibly allocate the embedding data. In this way, the JPEG steganography could be formulated as the optimization problem of minimizing the overall distortion cost in its decompressed spatial domain, which is equivalent to maximizing its statistical undetectability against JPEG phase-aware steganalysis features. Experimental results show that the proposed DCDT equipped with HiLL (a spatial steganographic distortion cost function) is superior to other state-of-the-art JPEG steganographic schemes, e.g., UERD, J-UNIWARD, and GUED in resisting the detection of JPEG phase-aware feature-based steganalyzers GFR and SCA-GFR, and rivals BET-HiLL with one order of magnitude lower computational complexity, along with the possibility of being further improved by considering the mutually dependent embedding interactions. In addition, the proposed DCDT is also verified to be effective for different image databases and quality factors.