In the field of image steganography research, more and more attention is paid to the importance of stego image robustness. In order to make steganography accessible from laboratory to practical applications, it becomes critical that the stego images can resist JPEG compression from transmission channel. In this paper, an image steganography algorithm with strong robustness to resist JPEG compression is proposed. First, the robust cover elements are selected using the sign of DCT coefficients which are kept constant before and after JPEG compression. Additionally, a distortion function and a weighted cost adjustment method are designed to assign an appropriate cost to each candidate DCT coefficient. Finally, the message is embedded in the cover image which has minimal embedding distortion by flipping the signs of DCT coefficients, while differential Manchester code is applied to the element positions to obtain the location feature. Compared with the prior art, our algorithm has better undetectability and stronger robustness, and it can resist the attacks from the social network platforms such as Facebook, Twitter, and WeChat.
In order to realize the act of covert communication in a public channel, steganography is proposed. In the current study, modern adaptive steganography plays a dominant role due to its high undetectability. However, the effectiveness of modern adaptive steganography is challenged when being applied in practical communication such as over social network. Several robust steganographic methods have been proposed while the comparative study between them is still unknown. Thus, we propose a framework to generalize the current typical steganographic methods resisting against compression attack, and meanwhile empirically analyze advantages and disadvantages of them based on four baseline indicators, referring to as capacity, imperceptibility, undetectability, and robustness. More importantly, the robustness performance of the methods is compared in the real application such as on Facebook, Twitter, and WeChat, which has not been comprehensively addressed in this community.
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