# High-Fidelity Steganography: A Covert Parity Bit Model-Based Approach
## 4 Proposed Scheme
### Data Embedding

Table 5: Comparison of the maximum bpp and PSNR values for different _high capacity_ methods. The highest bpp and PSNR values are highlighted in bold. corresponds to the percentage of the affected pixels to the total numbers of pixels. The salt and pepper attack is shown in Figures 7-12. On the other hand, in the data loss tampering attack we removed a squared area from the stego image, as shown in Figures 13 and 14. The proposed hiding scheme was tested with two different densities of 0.001 and 0.005 for the salt and pepper attack. It was determined after several experiments that the scale factor \(k\) represents a tuning parameter between stego quality and extraction quality. Figures 7-10 clearly show the trade-off problem with the salt and pepper attack and tampering (data loss) attack under different densities. Based on these figures, it is clear that the stego quality is enhanced when increasing the scale factor \(k\). In addition, the quality of the recovered secret is enhanced with the increase in the scale factor \(k\). However, there is a saturation point around \(k=5\) after which the quality of the recovered secret image decreases. A visual illustration of the attacked stego images and the recovered secret images is shown in Figures 11-14. For illustration purposes, in these experiments the secret image hidden is not the \"Rose\" secret image but is instead a different secret image named \"Handwriting\", as the \"Handwriting\" secret image contains written text. It is clear from Figure 14 that the text written in the \"Handwriting\" secret image remains readable after extraction, even when subjected to a tampering attack against a large \(256\times 256\) squared region. Figure 11: Results showing the extracted image after attacking the carrier image with salt and pepper attack using a density of 0.001. The experiment was conducted with different scaling factors \(k\) ranging from 1 to 20. Figure 10: Tampering attack against 50% of the stego image (dimension percentage) under different scale values \(k\) in the range [1; 2; 3; 4; 50]. (**a**) shows the PSNR values between the recovered and the original secret image. (**b**) shows the PSNR values between the cover and the stego image. Figure 12: Results showing the extracted image after attacking the carrier image with salt and pepper attack using a density of 0.0001. The experiment was conducted with different scaling factors \(k\) ranging from 1 to 20. Figure 13: Results showing the extracted image after tampering attack on the carrier image using and \(80\times 80\) block. The experiment was conducted with different scaling factors \(k\) ranging from 1 to 20. Figure 14: Results showing the extracted image after tampering attack on the carrier image using a \(256\times 256\) block. The experiment was conducted with different scaling factors \(k\) ranging from 1 to 20. ### Security

This subsection examines the security level of the proposed hiding scheme using a Convolutional Neural Network (CNN)-based steganalysis technique. Steganalysis is the science of detecting the existence of the secret data in stego signals and determining whether a given test image contains embedded secret data (i.e., stego signal) or contains no such embedded secret data (i.e., cover signal). One of the earliest attempts to develop a model-based steganography scheme was the model-based MB1 scheme reported in [42]. This scheme is based on modeling the LSB plane with the assistance of the Generalized Cauchy Distribution (GCD). However, because there is no ideal model that can perfectly regenerate a copy version of the cover image, there are noticeable differences between the original cover signal and the model-generated signal; therefore, MB1 is easily broken using the first-order statistical analysis [43]. Moreover, the MB1 scheme suffers from 'blockiness' artifacts between the original cover image and the stego image generated by the MB1 scheme. Therefore, an enhanced version called MB2 with de-blocking features was proposed in [42].