Robust Steganography for High Quality Images
Kai Zeng, Kejiang Chen, Weiming Zhang, Yaofei Wang, Nenghai Yu
Abstract
With the prosperity of online social networks (OSNs), people usually share photos taken with their mobile phones to OSN, which is suitable for covert communication. However, these images have high quality factors (QFs) and will be JPEG recompressed with low QFs by OSNs, which precludes existing robust steganography methods using low QF images. Therefore, we propose a Postprocessing and precise dither Modulation based robust Adaptive Steganography method (PMAS) for high quality images. Precise dither modulation ensures the robustness of the modified coefficients and improves security by reducing the magnitude of modifications. Postprocessing amends the coefficients that changed after recompression to ensure the robustness of unmodified coefficients. Additionally, we devise heuristics to mitigate post-processing and explore the relationship between the modification magnitude and distortion assignment with novel scaling functions, which all contribute to security. The experimental results demonstrate that PMAS is competent for high quality images, and the effect of every module in PMAS is verified.