Model-Based Non-Independent Distortion Cost Design for Effective JPEG Steganography
Abstract: Recent achievements have shown that model-based steganographic schemes hold promise for better security than heuristic-based ones, as they can provide theoretical guarantees on secure steganography under a given statistical model. However, it remains a challenge to exploit the correlations between DCT coefficients for secure steganography in practical scenarios where only a single compressed JPEG image is available. To cope with this, we propose a novel model-based steganographic scheme using the Conditional Random Field (CRF) model with four-element cross-neighborhood to capture the dependencies among DCT coefficients for JPEG steganography with symmetric embedding. Specifically, the proposed CRF model is characterized by the delicately designed energy function, which is defined as the weighted sum of a series of unary and pairwise potentials, where the potentials associated with the statistical detectability of steganography are formulated as the KL divergence between the statistical distributions of cover and stego. By optimizing the constructed energy function with the given payload constraint, the non-independent distortion cost corresponding to the least detectability can be accordingly obtained. Extensive experimental results validate the effectiveness of our proposed scheme, especially outperforming the previous independent art J-MiPOD.
Primary Subject Area: [Experience] Multimedia Applications
Relevance To Conference: Digital steganography is an important branch of information hiding that utilizes the data redundancy inherent in various types of digital media, as well as the physiological and psychological characteristics of human perception organs, to embed secret messages into the public digital media with certain coding, and then transmit the digital media containing the secret messages to achieve covert communication. This paper is dedicated to the study of JPEG image steganography, which involves various image processing techniques, such as image modeling, image filtering, and JPEG image decompression. The results of this research can not only be applied to image processing tasks, but also can be promoted on large video processing. The results of this work can not only be applied to image processing tasks, but also can be extended to video processing. We believe that this research is conducive to the advancement of multimedia processing.
Submission Number: 5560
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