Publication Type : Journal Article
Publisher : Advances in Intelligent Systems and Computing
Source : Advances in Intelligent Systems and Computing, Springer Verlag, Volume 515, p.777-785 (2017)
ISBN : 9789811031526
Keywords : Computation theory, Geometric operations, Image processing, Intelligent computing, Markov feature, PSNR, Radiometric operations, Singular value decomposition, SSIM, Steganography
Campus : Coimbatore
School : School of Engineering
Center : TIFAC CORE in Cyber Security
Department : Computer Science, Mathematics, cyber Security
Year : 2017
Abstract : Steganography is an art of hiding of secret information in an innocuous medium like an image. Most of the current steganographic algorithms hide data in the spatial or transform domain. In this paper, we perform attacks on three singular value decomposition-based spatial steganographic algorithms, by applying image processing operations. By performing these attacks, we were able to destroy the stego content while maintaining the perceptual quality of the source image. Experimental results showed that stego content can be suppressed at least by 40%. PSNR value was found to be above 30 dB and SSIM obtained was 0.61. Markov feature and BER are used to calculate the percentage of stego removed. © Springer Nature Singapore Pte Ltd. 2017.
Cite this Research Publication : P. P. Amritha, Ravi, R. P., and Dr. M. Sethumadhavan, “Active steganalysis on svd-based embedding algorithm”, Advances in Intelligent Systems and Computing, vol. 515, pp. 777-785, 2017.