Color Image Stegananalysis Using Correlations between RGB Channels

Abstract : Digital images, especially color images, are very widely used, as well as traded via Internet, e-mail and posting on websites. Images have a large size which allows embedding secret messages of large size, so they are a good medium for digital steganography. The main goal of steganalysis is to detect the presence of hidden messages in digital media. In this paper, we propose a steganalysis method based on color feature correlation and machine learning classification. Fusing features with features obtained from color-rich models allows to increase the detectability of hidden messages in the color images. Our novel proposition uses the correlation between different channels of color images. Features are extracted from the channel correlation and co-occurrence correlation. In this work, all stego images are created with a range of different payload sizes using two steganography S-UNIWARD and WOW algorithms. To validate the proposed method, his efficiency is demonstrated by comparison with color rich model steganalysis.
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Communication dans un congrès
IWCC: International Workshop on Cyber Crime, Aug 2015, Toulouse, France. 4th International Workshop on Cyber Crime, IWCC'2015, co-located with 10th International Conference on Availability, Reliability and Security - ARES 2015, 2015, 〈http://stegano.net/IWCC2015/〉. 〈10.1109/ARES.2015.44〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01234229
Contributeur : Marc Chaumont <>
Soumis le : jeudi 26 novembre 2015 - 14:43:09
Dernière modification le : jeudi 24 mai 2018 - 15:59:23
Document(s) archivé(s) le : samedi 27 février 2016 - 13:07:19

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Hasan Abdulrahman, Marc Chaumont, Philippe Montesinos, Baptiste Magnier. Color Image Stegananalysis Using Correlations between RGB Channels. IWCC: International Workshop on Cyber Crime, Aug 2015, Toulouse, France. 4th International Workshop on Cyber Crime, IWCC'2015, co-located with 10th International Conference on Availability, Reliability and Security - ARES 2015, 2015, 〈http://stegano.net/IWCC2015/〉. 〈10.1109/ARES.2015.44〉. 〈lirmm-01234229〉

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