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Nowadays, people are sharing their pictures on online social networks (OSNs),so OSN is a good platform for Steganography. But OSNs usually perform JPEGcompression on the uploaded image, which will invalidate most of the existingsteganography algorithms. Recently, some works try to design robuststeganography which can resist JPEG compression, such as DitherModulation-based robust Adaptive Steganography (DMAS) and Generalized ditherModulation-based robust Adaptive Steganography (GMAS). They relieve the problemthat the receivers cannot extract the message correctly when the quality factorof channel JPEG compression is larger than that of cover images. However, theyonly can realize limited resistance to detection and compression due to robustdomain selection. To overcome this problem, we meticulously explore three lossyoperations in the JPEG recompression and discover that the key problem isspatial overflow. Then two preprocessing methods Overall Scaling (OS) andSpecific Truncation (ST) are presented to remove overflow before messageembedding as well as generate a reference image. The reference image isemployed as the guidance to build asymmetric distortion for removing overflowduring embedding. Experimental results show that the proposed methodssignificantly surpass GMAS in terms of security and achieve comparablerobustness.

Improving Dither Modulation based Robust Steganography by Overflow Suppression