Back close

Active steganalysis on svd-based embedding algorithm

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)

Url :

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, cyber Security, Mathematics

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.

Admissions Apply Now