Improved JPEG Phase-Aware Steganalysis Features Using Multiple Filter Sizes and Difference Images

In terms of feature-based steganalysis for JPEG images, JPEG phase-aware features (e.g., DCTR and GFR) currently provide the best detection performance on modern adaptive steganographic schemes. But in DCTR and GFR, the types of residual images are relatively single. They only use the convolution residuals obtained with the DCT or Gabor filters of fixed size 8 × 8. In this paper, to further improve DCTR and GFR, two strategies are proposed to enrich the features by diversifying residual images, and the corresponding symmetrization rules for the features are also elaborately designed. First, instead of a single filter size of 8 × 8, convolution filters of multiple sizes are adopted to generate different residual images. Second, we also compute JPEG phase-aware features from the difference images between two convolution residuals. Since the features from convolution residuals and difference images are diverse and complementary, the combination of these two kinds of features can significantly improve the detection accuracy. Last but not least, different symmetrization rules are accordingly designed for these features by considering filter types, filter sizes, and residual subtraction to decrease the feature dimension and enhance the feature robustness. The experimental results demonstrate the effectiveness of our proposed features, and we can further boost the performance by incorporating the knowledge of the selection channel and using the accelerated weighted histogram method.