LAUSR

Due to a large number of user-uploaded images, social networks have become secure channels for covert communication. However, the JPEG recompression of social networks changes the DCT coefficients of stego images, resulting in the failure of adaptive steganography. To achieve steganography in lossy channels, robust steganography has been proposed. In this letter, the ability against JPEG recompression of robust steganography is further improved by introducing a robustness cost function. For calculating the robustness cost, a robustness model based on the spatial domain calculated from DCT coefficients is firstly proposed. Then the robustness cost is acquired by measuring the distance between the spatial pixels calculated from modified DCT coefficients and the robustness model adjusted spatial pixels. Combining the distortion function and the robustness cost function, the method proposed has considerable robustness performance while maintaining satisfying security performance. Experimental results show that with the maximum reduction of 4.04% on security performance, the algorithm proposed has a significant improvement on robustness performance compared with state-of-the-art robust steganography.