Research Article
A Novel Technique of Steganalysis in Uncompressed Image through Zipf’s Law
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 40 - Issue 6 |
| Published: February 2012 |
| Authors: Laimeche Lakhdar, Hayet Farida Merouani |
10.5120/4957-7211
|
Laimeche Lakhdar, Hayet Farida Merouani . A Novel Technique of Steganalysis in Uncompressed Image through Zipf’s Law. International Journal of Computer Applications. 40, 6 (February 2012), 1-8. DOI=10.5120/4957-7211
@article{ 10.5120/4957-7211,
author = { Laimeche Lakhdar,Hayet Farida Merouani },
title = { A Novel Technique of Steganalysis in Uncompressed Image through Zipf’s Law },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 40 },
number = { 6 },
pages = { 1-8 },
doi = { 10.5120/4957-7211 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A Laimeche Lakhdar
%A Hayet Farida Merouani
%T A Novel Technique of Steganalysis in Uncompressed Image through Zipf’s Law%T
%J International Journal of Computer Applications
%V 40
%N 6
%P 1-8
%R 10.5120/4957-7211
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In this paper, we present a Novel method to detect the existence of hidden message in LSB steganography. The key element of the proposed method is the power Law: Zipf’s law.The detection theory is based on statistical analysis of pixel patterns using a Zipfness measure between successive bit planes. The basic idea is that, the correlation between bit planes as well as the binary texture characteristics within the bit planes will differ between a stego image and a cover image. The seventh and eighth bit planes, and possibly others, are used to calculate the Zipf Quality (ZQ) measure. The proposed technique does not need a reference image and it works with spatial transform-domain embedding. The method is similar to steganalysis in [12]; it exploits Binary Similarity measures of images to reveal the presence of steganographic content.
References
- Xuan, Z., HweeHwa, P., and Kian, L. 2004. Hiding Data Accesses in Steganographic File System. ICDE, 572-583.
- Andreas, W., Andreas, P. 1999. Attacks on steganographic systems. In 3rd Info. Hiding Workshop, Dresden, Germany, vol. 1768, vol. 1768.
- Fridrich, J., Goljan, M. and Du, R. 2001. Reliable Detection of LSB Steganography in Color and Grayscale Images. In ACM Workshop on Multimedia and Security, 27–30.
- Niels, P. 2001. Defending Against Statistical Steganalysis. In 10th USENIX Security Symposium, 323–336.
- Andreas, W. 2001. High Capacity Depsite Better Steganalysis: F5- a Steganographic Algorithm. In Fourth Information Hiding Workshop, 301–315.
- Fridrich, J., Miroslav, G. and Dorin, H. 2002. Attacking the Outguess. In ACM Workshop on Multimedia and Security.
- Goljan, M., Fridrich, J. and Dorin, H. 2003. New Methodology for Breaking Steganographic Methods for Jpegs. In EI SPIE, Santa Clara, CA.
- Fridrich, J., Goljan, M. and Soukal, D. 2003. Higher-order Statistical Steganalysis of Palette Images. In EI SPIE, Santa Clara, CA.
- Goljan, M., Fridrich, J. and Dorin, H. 2002. Steganalysis of Jpeg Images: Breaking the f5 Algorithm. In 5th Information Hiding Workshop.
- Farid, H. and Siwei, L. 2002. Detecting Hidden Messages using Higher-Order Statistics and Support Vector Machines. In Pre-proceedings 5th Information Hiding Workshop.
- Avcibas, I., Memon, N., and Sankur, B. 2001. Steganalysis using Image Quality Metrics. In Security and Watermarking of Multimedia Contents, SPIE. San Jose, CA.
- Avcibas, I., Memon, N., and Sankur, B. 2002. Image Steganalysis with Binary Similarity Measures. In IEEE International Conference on Image Processing, Rochester, New York.
- Kobsi N., Merouani, F.H. 2007. Neural Network Based Image Steganalysis: A Comparative study. In JIG’2007. Constantine, Algeria,
- Laimeche, L., Merouani, F.H. 2010. Detection Hidden Messages using Zipf's Law. 3rd International Conference on Software, Knowledge, Information Management and Applications (SKIMA’09) Fes, Morocco.
- ZIPF, G.K. 1949. Human Behavior and the Principle of "Least Effort". Addison-Wesley, New York.
- Caron, Y. , Makris, P., and Vincent, N. 2002. A Method for Detecting Artificial Objects in Natural Environmements. International Conference on Pattern recognition (ICPR - IAPR), Québec (Canada). 600-603.
- Vincent, N., Makris, P., and Brodier, J. 2000. Compressed Image Quality and Zipf’s Law. Proceedings of International Conference on Signal Processing (ICSP – IFIC-IAPRWCC2000), Pékin (Chine). 1077-1084.
- Bi, D., Asselin, J.P., and Mraghni, M. 1996. Spatial Gray Levels Distribution based Unsupervised Texture Segmentation. Proceedings of 3rd International Conference of Signal Processing (ICSP96), Pékin (Chine).
- Makris, P., Vincent, N. 2000. Zipf’s law: a Tool for Image Characterization. Vision Interface'2000, Montreal (Canada). 262-268.
- Caron, Y., Vincent, N., and Makris, P. 2003. Measuring Compressed Image Quality using Zipf's Law. RFAI, CORESA’03, Lyon (France). 239-242.
- Memon, N., Chandramouli, R. 2001. Analysis of LSB Based Image Steganography techniques. In Proceedings of the International Conference on Image Processing, Thessaloniki Greece.
- Dumitrescu, S., Wu, X., and Wang, Z. 2003. Detection of LSB Steganography via Sample Pair Analysis. In IEEE transactions on Signal Processing. 1995-2007.
- Dumitrescu, S., Wu, X., and Memon, N. 2002. On steganalysis of Random LSB Embedding in Continuous-tone Images. ICIP (3). 641-644.
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