A Novel Gradient-guided Post-processing Method for Adaptive Image Steganography

Xie, Guoliang; Ren, Jinchang; Marshall, Stephen; Zhao, Huimin; Li, Rui

doi:10.1016/j.sigpro.2022.108813

Cited by 15 publications

(1 citation statement)

References 40 publications

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“…Image steganography algorithms are generally divided into two categories: non-adaptive steganography and adaptive steganography [6,7,8,9,10,11,12,13,14,15,16,17]. Non-adaptive steganographic algorithms like Least Significant Bit replacement (LSBr) and Least Significant Bit matching (LSBm) steganography, only randomly embed secret message by modifying pixels/coefficients of the image, where selection of embedding position is nearly independent of image content.…”

Section: Introductionmentioning

confidence: 99%

Robust Steganography in Practical Communication: A Comparative Study

Qiao

Sheng-wang

Wang

et al. 2023

Preprint

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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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