A Robust Watermarking using Blind Source Separation
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A Robust Watermarking using Blind Source Separation

Authors: Anil Kumar, K. Negrat, A. M. Negrat, Abdelsalam Almarimi

Abstract:

In this paper, we present a robust and secure algorithm for watermarking, the watermark is first transformed into the frequency domain using the discrete wavelet transform (DWT). Then the entire DWT coefficient except the LL (Band) discarded, these coefficients are permuted and encrypted by specific mixing. The encrypted coefficients are inserted into the most significant spectral components of the stego-image using a chaotic system. This technique makes our watermark non-vulnerable to the attack (like compression, and geometric distortion) of an active intruder, or due to noise in the transmission link.

Keywords: Blind source separation (BSS), Chaotic system, Watermarking, DWT.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058593

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References:


[1] J. Daemen and V.Rijmen, The Design of Rijndael, AES - Advanced Encryption Standard}, ISBN 3-540-42580-2 (Springer-Verlag Berlin Heidelberg, New York).
[2] "Data Encryption Standard (DES)," National Bureau Standards FIPS Publication 46(1977).
[3] R. L. Rivest, A. Shamir, and L. Adleman, A method for obtaining digital signatures and public key cryptosystems, Commun. Assoc. Comput.(1978)120-126.
[4] R.L. Pickholtz, D.L. Schilling, and L.B. Millstein, Theory of spread spectrum communication- A tutorial, IEEE trans. Commun. , 30(1982) 885-884.
[5] I. J. Cox, J. Kilian , F. Thomson, T. Shamoon , Secure Spread Spectrum Watermarking for Multimedia, IEEE trans of Image Processing, 6( 12),(1997) 1673-1687.
[6] G. W. Braudaway, K. A. Magerlein , and F. C. Mintzer, Color correct digital watermarking of images, U.S. Patent 5 530759, 1996.
[7] C. S. Rai and Yogesh Singh, Source distribution models for blind source separation, Neurocomputing , 57C, (2004)501-505.
[8] C. S. Rai and Yogesh Singh, Blind source separation: a statistical approach, Neural Network World, 12 (3-4),(2003) 173-177.
[9] Yogesh Singh and C. S. Rai, Blind source separation: a unified approach, Neurocomputing, 49(1-4),(2002)435-438.
[10] A. Swindlehurst, M. Goris and B.Otterson, Some experiments with array data collected in actual urban and sub-urban environment, IEEE Workshop on Signal Processing Advances in Wireless Communication,( 1997), 301-304.
[11] L. De. Lathauwer, B.De. Moor and J. Vandewalle, Fetal eletrocardiogram extraction by source sub-space separation, Proc. HOS-95, Spain, (1995), 134-138.
[12] A. J. Bell and T. J. Sejnowskim, Edges are the ÔÇÿIndependent components- of natural scenes, Advances in Neural Information Processing Systems, vol. 9, (MIT Press, 1996).
[13] W. Kasprzak and A. Chichochi, Hidden image separation from incomplete image mixtures by independent component analysis, in Proc. Of the 13th Int. Conf. on Pattern Recognition, 2 , (1996).394-398
[14] Q. H. Lin and F. L. Yin, Blind source separation applied to image cryptosystems with dual encryptions, Electronics Letters, 38(19), (2002) 1092-1094.
[15] Q. H. Lin and F. L. Yin, Image cryptosystems based on blind source separation, Proc. IEEE Int. cnof. Neural networks & Signal Processing, Vol. 2, ( 2003) 1366-1369.
[16] C.W. Wu and N. F. Rulkov, "Studying chaos via 1-DmapsÔÇöa tutorial," IEEE Trans. on Circuits and Systems I: Fundamental Theory and Applications, vol. 40, no. 10, pp. 707-721, 1993.
[17] Anil Kumar and Navin Rajpal, Application of T-Code, Turbo Codes and Pseudo-Random Sequence for Steganography, Journal of Computer Science 2 (2):148-153, 2006.
[18] Anil kumar and Navin Rajpal, Secret Image Sharing Using Pseudo- Random Sequence, IJCSNS International Journal of Computer Science and Network Security, Vol. 6 No.2B(2006), 185-193.