Randomized Symmetric Crypto Spatial Fusion Steganographic System
DOI:
https://doi.org/10.5614/itbj.ict.res.appl.2016.10.1.2Abstract
The image fusion steganographic system embeds encrypted messages in decomposed multimedia carriers using a pseudorandom generator but it fails to evaluate the contents of the cover image. This results in the secret data being embedded in smooth regions, which leads to visible distortion that affects the imperceptibility and confidentiality. To solve this issue, as well as to improve the quality and robustness of the system, the Randomized Symmetric Crypto Spatial Fusion Steganography System is proposed in this study. It comprises three-subsystem bitwise encryption, spatial fusion, and bitwise embedding. First, bitwise encryption encrypts the message using bitwise operation to improve the confidentiality. Then, spatial fusion decomposes and evaluates the region of embedding on the basis of sharp intensity and capacity. This restricts the visibility of distortion and provides a high embedding capacity. Finally, the bitwise embedding system embeds the encrypted message through differencing the pixels in the region by 1, checking even or odd options and not equal to zero constraints. This reduces the modification rate to avoid distortion. The proposed heuristic algorithm is implemented in the blue channel, to which the human visual system is less sensitive. It was tested using standard IST natural images with steganalysis algorithms and resulted in better quality, imperceptibility, embedding capacity and invulnerability to various attacks compared to other steganographic systems.
Downloads
References
Harmsen, J. & Pearlman, W., Steganalysis of Additive Noise Modelable Information Hiding, Proc. SPIE Electronic Imaging, 50(20), pp. 131-142, 2003.
Xydeas, C.S. & Petrovic, V., Gradient based Multiresolution Image Fusion, IEEE Transactions on Image Processing, 13(2), pp. 228-237, 2004.
Toet, A., Image Fusion by a Ratio of Low-pass Pyramid, Pattern Recognition Letters, (9), pp. 245-253, 1989.
Viswanathan, P. & Venkata Krishna, P., Text Fusion Watermarking in Medical Image with Semi-reversible for Secure Transfer and Authentication, Advances in Recent Technologies in Communication and Computing, IEEE explore, pp. 585-589, Oct. 2009.
Viswanathan, P. & Venkata Krishna, P., Fusion of Cryptographic Watermarking Medical Image System with Reversible Property, ICTACT Int J. on Image and Video Processing, 2(1), pp. 258-263, 2011.
Viswanathan, P. & Venkata Krishna, P., Medical Image Spatial Fusion Watermarking System, Signal and Image Processing, Lectures Notes in Electrical Engineering, 222, pp. 453-464, 2013.
Viswanathan, P. & Venkata Krishna, P., A Joint FED Watermarking System using Spatial Fusion for Verifying the Security Issues of Teleradiology, Biomedical and Health Informatics, IEEE Journal of, 18, (3), pp. 753- 764, 2014.
Ker, A., Improved Detection of LSB Steganography in Grayscale Images, Lecture Notes in Computer Science, International Workshop on Information Hiding, eds. Fridrich, pp. 97-115, 2004.
Chan, C-K. & Cheng, L-M., Hiding Data in Images by Simple LSB Substitution, Pattern Recognition letter, 37(3), pp. 469-474, 2004.
Ker, A.D., Steganalysis of LSB Matching in Grayscale Images, IEEE Signal Process. Letter 12(6), pp. 441-444, 2005.
Pevny, T., Filler, T. & Bas, P. Using High-dimensional Image Models to Perform Highly Undetectable Steganography, Lecture Notes in Computer Science: 12th International Conference on Information Hiding, (ed.(s)). Safavi-Naini R, Bhme R, Fong PWL, pp. 161-177, 2010.
Ker, A.D., Steganalysis of Embedding in Two Least-significant Bits, IEEE Trans. Inf. Forensics Security 2(1), 46-54, 2007.
Westfeld, A. & Pfitzmann, A., Attack on Steganographic Systems, Lectures Notes in Computer Science, 1768, pp. 61-75, 2000.
Fridrich, J., Goljan, M. & Du, R., Detecting LSB Steganography in color, and gray-scale images, IEEE Multimedia, 8(4), pp. 22-28, Oct. 2001.
Dumitrescu, S., Wu, X. & Wang, Z., Detection of LSB Steganography via Sample Pair Analysis, IEEE Trans. Signal Process., 51(7), pp. 1995-2007, 2003.
Wu, D. & Tsai, W., A Steganographic Method for Images by Pixel Value Differencing, Pattern Recognit. Letter, 24, pp. 1613-1626, 2003.
Zhang, X. & Wang, S., Vulnerability of Pixel-value Differencing Steganography to Histogram Analysis and Modification for Enhanced Security, Pattern Recognit. Letter, 25, pp. 331-339, 2004.
Yang, C.H., Weng, C.Y., Wang, S.J. & Sun, H.M., Adaptive Data Hiding in Edge Areas of Images with Spatial LSB Domain Systems, IEEE Trans. Inf. Forensics Security, 3(3), pp. 488-497, 2008.
Hempstalk, K., Hiding behind corners: Using Edges in Images for Better Steganography, Proc. Computing Women's Congress, Hamilton, New Zealand, 2006.
Kouider, S., Chaumont, M. & Puech, W., Adaptive Steganography by Oracle (ASO), IEEE International Conference on Multimedia and Expo (ICME), pp. 1-6, July 2013
Holub, V., Fridrich, J. & Denemark, T., Universal Distortion Function for Steganography in an Arbitrary Domain, EURASIP J. Inform. Security, 2014(1), 2014.
Filler, T. & Fridrich, J., Design of Adaptive Steganographic Schemes for Digital Images, Media Watermarking, Security, and Forensics XIII, Part of IS&T SPIE Electronic Imaging Symposium, 7880, pp. 1-14, 2011
Luo, W., Huang, F. & Huang, J., Edge Adaptive Image Steganography Based on LSB Matching Revisited, IEEE Trans. Inf. Forensics Security 5(2), pp. 201-214, 2010.
IST image data set http://wang.ist.psu.edu/docs/related/downloads (9 November 2013).
Steganography attack tools http://guillermito2.net/stegano/tools/ (9 November 2013).
