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A Novel Adaptive Steganographic Technique using Kohonen Neural Network based on Integer Wavelet Transform
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 59 - Number 17 |
| Year of Publication: 2012 |
| Authors: Liya Lesly, Rajesh Cherian Roy |
10.5120/9637-4303
|
Liya Lesly, Rajesh Cherian Roy . A Novel Adaptive Steganographic Technique using Kohonen Neural Network based on Integer Wavelet Transform. International Journal of Computer Applications. 59, 17 ( December 2012), 1-5. DOI=10.5120/9637-4303
Abstract
Steganography allows us to hide a desired confidential information in a covered or host image while image encryption is decomposing the desired information to a non-readable, non-comprehended manner. Steganography gained importance in the past few years due to the increasing need for providing secrecy in an open environment like the internet. This is made possible by hiding the very existence of the message and makes communication undetectable. Steganography is the science of secret message delivery using cover media and has many technical challenges such as high hiding capacity and security. In this paper, a method is proposed to optimize these two requirements by suggesting a novel technique for hiding data in digital images. For this, an adaptive hiding capacity function along with a Kohonen neural network has been employed. This method hides secret data in Integer wavelet coefficients. The Optimal pixel adjustment (OPA) algorithm is applied after embedding the message. A new high capacity image steganographic method based on Kohonen neural network is also introduced. Kohonen network is trained according to the absolute contrast sensitivity of pixels present in cover image. On the receiving side, the original image is not needed for extracting the embedded data. It is observed that the capacity and security is increased with acceptable PSNR and hiding capacity.
References
- R. J. Anderson, M. G. Khun, "Information hiding- A survey", Proceedings of IEEE, Vol. 87, 1999
- R. O. El Safy, H. H. Zayed, A. El Dessouki, "An Adaptive Steganographic Technique Based on Integer Wavelet Transform", International Conference on Networking and Media Convergence, 2009.
- H. W. Tseng and C. C. Chnag, "High capacity data hiding in jpeg compressed images", Informatica, Vol. 15, 2004.
- ] C. K. Chan and L. M. Chang, "Hiding data in images by simple LSB substitution", Pattern Recognition, pp. 469-474, March 2004.
- N. Wu and M. Hwang, "Data hiding: current status and key issues", International Journal of Network Security, Vol. 14, pp. 1-9, Jan 2007.
- W. Chen, " A comparative study of information hiding schemes using amplitude, frequency and phase embedding", PhD thesis, National Cheng Kung University, Taiwan, May 2003.
- Elham Ghasemi, Jamshid Shanbehzadeh, Bahram Zahir Azami, "A steganographic method based on Integer wavelet transform and genetic algorithm", International Conference on Communications and Signal Processing, 2011.
- Arun Rana,Nitin Sharma, Amandeep Kaur, "Image steganogrphy based on Kohonen neural network", International Journal of Engineering Research and Applications (IJERA), Vol. 2, Issue 3, May-Jun 2012, pp. 2234-2236.
- Michael David Adams, "Reversible Integer-to-Integer Wavelet Transforms for Image Coding", PhD thesis, University of British Columbia, Sep 2002.
- Geert Uytterhoeven, Dirk Roose, Adhemar Bultheel, "Integer Wavelet Transforms using the Lifting Scheme", Department of Computer Science, International Conference on Communication systems and Computers, Vol. 1, pp. 6251-6253. .
- Kohonen. T, "Self-Organizing and Associative Memory", Springer-Verlag,Heidelberg.
- B. Lai and L. Chang, "Adaptive Data Hiding for Images based Haar Discrete Wavelet Transform", Lecture noted in Computer Science, Vol. 4319/2006.
- H. H. Zayed, "A High-Hiding Capacity Technique for Hiding Data in Images based on K-bit LSB substitution", International Conference on Artificial Intelligence Applications, Cairo, Feb. 2005.
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