Steganography by Minimizing Statistical Detectability: The cases of JPEG and Color Images
Author(s) -
Rémi Cogranne,
Quentin Giboulot,
Patrick Bas
Publication year - 2020
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
ISBN - 978-1-4503-7050-9
DOI - 10.1145/3369412.3395075
Subject(s) - jpeg , steganography , discrete cosine transform , computer science , artificial intelligence , embedding , computer vision , transform coding , gaussian , pattern recognition (psychology) , image (mathematics) , physics , quantum mechanics
This short paper presents a novel method for steganography in JPEG-compressed images, extended the so-called MiPOD scheme based on minimizing the detection accuracy of the most-powerful test using a Gaussian model of independent DCT coefficients. This method is also applied to address the problem of embedding into color JPEG images. The main issue in such case is that color channels are not processed in the same way and, hence, a statistically based approach is expected to bring significant improvements when one needs to consider heterogeneous channels together.The results presented show that, on the one hand, the extension of MiPOD for JPEG domain, referred to as J-MiPOD, is very competitive as compared to current state-of-the-art embedding schemes. On the other hands, we also show that addressing the problem of embedding in JPEG color images is far from being straightforward and that future works are required to understand better how to deal with color channels in JPEG images.
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