Research Article
An Efficient DCT-SVD Steganographic Approach Applied to JPEG Images
@ARTICLE{10.4108/eai.28-9-2020.166365, author={Franklin Tchakount\^{e} and Priva Chassem Kamdem and Jean Claude Kamgang and Hortense Boudjou Tchapgnouo and Marcellin Atemkeng}, title={An Efficient DCT-SVD Steganographic Approach Applied to JPEG Images}, journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems}, volume={7}, number={24}, publisher={EAI}, journal_a={INIS}, year={2020}, month={9}, keywords={Image steganography, JPEG, Discrete Cosine Transform, Insertion, Singular Value Decomposition, Quantization, Attacks, Social media}, doi={10.4108/eai.28-9-2020.166365} }- Franklin Tchakounté
Priva Chassem Kamdem
Jean Claude Kamgang
Hortense Boudjou Tchapgnouo
Marcellin Atemkeng
Year: 2020
An Efficient DCT-SVD Steganographic Approach Applied to JPEG Images
INIS
EAI
DOI: 10.4108/eai.28-9-2020.166365
Abstract
To prove the origin of images in social media, this work proposes an efficient JPEG image steganography approach. After structuring the cover image into blocks of 8*8 pixels, Discrete Cosine Transform is applied to each block of pixels. The latter are quantified using a quantization table and a matrix of DC coefficients from quantized blocks of pixels, is obtained. Singular Value Decomposition is applied to the previous matrix and the secret message is inserted within singular vectors. For extraction purposes, previous transformations are followed reversely. An experimentation is made on seven images and results show that the proposed system outperforms similar studies in three aspects (i) it preserves stego image quality with PSNR of stego images varying between 38 and 54 (ii) it is able to insert a secret message of 257600 bits with the capacity of 4 bits per pixel (iii) it is robust and resistant to attacks such as histogram analysis and chi-square test.
Copyright © 2020 Franklin Tchakounté et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
