Secure Information Transmission using Steganography and Morphological Associative Memory
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10.5120/9940-4572 |
Sara Nazari, Amir-masoud Eftekhari and Mohammad Shahram Moin. Article: Secure Information Transmission using Steganography and Morphological Associative Memory. International Journal of Computer Applications 61(7):23-29, January 2013. Full text available. BibTeX
@article{key:article,
author = {Sara Nazari and Amir-masoud Eftekhari and Mohammad Shahram Moin},
title = {Article: Secure Information Transmission using Steganography and Morphological Associative Memory},
journal = {International Journal of Computer Applications},
year = {2013},
volume = {61},
number = {7},
pages = {23-29},
month = {January},
note = {Full text available}
}
Abstract
This paper presents a new steganography algorithm based on Morphology associative memory. Often, steganalysis methods are created to detect steganography algorithms using Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). In this paper, cover images are mapped to morphological representation by using morphology transform containing morphological coefficients, and each bit of secret message is inserted in the least significant bit of morphological coefficients. To evaluate stego quality, we measure the quality of the cover image after embedding by comparing with other image transformed steganography algorithms such as discrete cosine and Wavelet transforms. The quality of stego has considerably improved in comparison with the state-of-art methods. In the other experimentation, we test the robustness of our proposed method by using Wavelet and Block-based steganalysis methods. The results show a high level of robustness of our algorithm respect to other steganography algorithms.
References
- Abbas Cheddad, Joan Condell, Kevin Curran and Paul McKevitt, Digital image steganography: Survey analysis of current methods, Signal Processing(2010), pp. 727–752.
- Mahendra Kumar, Steganography and Steganalysis of JPEG Images, Ph. D. thesis, Florida,2011.
- Chin-Chen Chang, Ju-Yuan Hsiao and Chi-Shiang Chan, Finding optimal least-significant-bit substitution in image hiding by dynamic programming strategy, Pattern Recognition, vol. 36(2003), pp. 1583 – 1595.
- R. Z. Wang, C. F. Lin, J. C. Lin, Image hiding by optimal LSB substitution and genetic algorithm, Pattern Recognition 34 (2001) 671–683.
- Z. Xiong, O. G. Guleryuz, and M. T. Orchard, A DCT-based embedded image coder, IEEE Signal Processing Letters, vol. 3 (1996), pp. 289–290.
- S. Winograd, On computing the discrete Fourier transform, Proceedings of the National Academy of Sciences of the UnitedStates of America, vol. 73, no. 4 (1976), pp. 1005–1006.
- Ahmed A. Abdelwahab and Lobna A. Hassaan, A discrete wavelet transform based technique for image data hiding, 25th National radio science conference, 2008.
- M. F. Tolba, M. A. Ghonemy , I. A. Taha, A. S. Khalifa, Using Integer Wavelet Transforms In Colored Image Steganography, IJICIS Vol. 4 No. 2, July 2004.
- RajaVikas, VenugopalPatnaik. , High capacity lossless secure image steganography using wavelets,Proceeding of International Conference on Advanced Computing and Communications(2006), pp. 230–235.
- HediehSajedi, Mansour Jamzad, Using Contourlet Transform and Cover selection for secure Steganography. International Journal of Information Security (2010), vo. 9, Issue: 5, Publisher: Springer, pp. 1–16.
- Derek Upham, Jpeg-jsteg, http: //www . funet . fi/pub/crypt/steganography/jpeg-jsteg-v4. diff. gz. pp. 519–528, Cancun, Mexico.
- Andreas Westfeld, F5: a Steganographic Algorithm, Proceedings of the 4th International Workshop on Information Hiding, Springer-Verlag(2001), pp. 289-302.
- J. Fridrich, M. Goljan, and D. Hogea, Attacking the Outguess, Binghamton University Press(2000).
- J. Serra, Image Analysis and Mathematical Morphology, vol. 2, Theoretical Advances, Academic Press, Boston,USA, 1988.
- G. X. Ritter and P. Sussner, An Introduction to Morphological Neural Networks, Proceedings of the 13th International Conference on Pattern Recognition (ICPR '96), vol. 4, August 1996, pp. 709–717, Vienna, Austria.
- G. X. Ritter, P. Sussner, and J. L. Diaz-de-Le on, Morphological Associative Memories, IEEE Transactions on Neural Networks, vol. 9, no. 2 (1998), pp. 281–293.
- E. Guzman, O. Pogrebnyak, C. Yanez, and J. A. Moreno, Image compression algorithm based on morphological associative memories, Proceedings of the 11th american Congress in Pattern Recognition (CIARP '06), vol. 4225
- Khalid Sayood, Introduction to Data Compression, second ed. , Academic Press, San Diego, CA, 2000.
- Yu-Chen Hu, Chin-Chen Chang,A new lossless compression scheme based on Huffman coding scheme for image compression, Signal Processing: Image Communication, Volume 16, Issue 4, November 2000, pp. 367-372.
- Image Database , http:// www. Image processing place. com / root _files_ V3/image _ databases . htm.
- http://www. cs. washington. edu/research/imagedatabase/groundtruth.
- Y. Linde, A. Buzo, and R. M. Gray, An algorithm for vector quantizer design, IEEE Transactions on Communications, vol. 28, no. 1(1980), pp. 84–95.
- R. Jain, R. Kasturi, B. G. Schunk, "Machine Vision", MIT press and McGrawhill 1995.
- Lyu. , Farid, Detecting hidden messages using higher-order statistics and support vector machines, Proceedings of 5th International Workshop on Information Hiding (2002).
- Seongho Cho, Byung-Ho Cha, Jingwei Wang and Jay Kuo, Block-Based Image Steganalysis: Algorithm and Performance Evaluation, IEEE International Symposium on Circuits and Systems (ISCAS) ( 2010), Paris, France.