Color Image Stegananalysis Using Correlations between RGB Channels - Archive ouverte HAL Access content directly
Conference Papers Year : 2015

Color Image Stegananalysis Using Correlations between RGB Channels

(1) , (2, 3) , (1) , (1)
1
2
3

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.
Fichier principal
Vignette du fichier
IWCC2015_ABDULRAHMAN_CHAUMONT_MONTESINOS_MAGNIER_color_steganalysis.pdf (2.1 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

lirmm-01234229 , version 1 (26-11-2015)

Identifiers

Cite

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. ⟨10.1109/ARES.2015.44⟩. ⟨lirmm-01234229⟩
231 View
1073 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More