Information Hiding Based on Histogram and Pixel Pattern
DOI:
https://doi.org/10.13052/2245-1439.642Keywords:
Steganography, Histogram, Mod bit algorithm, Pixel valueAbstract
Recently, information exchange using internet is increasing, such that information security is necessary for securing confidential information because it is possible to eavesdrop the information. There are several methods for securing the exchanged information such as was proposed by Rejani et al. Rejani’s method can be noiseless in low capacity but noisy in high capacity. In the case of high capacity, it will raise suspicion. This research proposed a method based on histogram and pixel pattern for keeping the stego image noiseless while still keeping the capacity high. Secret information can be embedded into the cover by evaluating the histogram and map the characters used in the secret message to the consecutive intensity in the cover image histogram. The map of the characters is sent to the recipient securely. Using the proposed method there is no pixel value changes during the embedding process. Based on the result of the experiments, it is shown that in noiseless condition, the proposed method has higher embedding capacity than Rejani’s especially when using cover image with sizes larger than 128 × 128. Thus, in noiseless condition the embedding capacity using the proposed method is higher than Rejani’s method in noiseless condition.
Downloads
References
Joseph, A., and Sundaram, V. (2011). Cryptography and steganography–a survey. Int. J. Comput. Sci. (Rabat). 2, 626–630.
Babita and Ayushi (2013). Secure image steganography algorithmusing RGB image format and encryption technique. Int. J. Sci. Environ. Technol. 4, 758–762.
Rejani, R., Murugan, D., and Krishnan, D. V. (2015). Pixel Pattern Based Steganography on Images. J. Image Video Process 5, 991–997.
James, C. (2001). Steganography Past, Present, Future. SANS Institute.
CH, M. V. R. (2015). Medical Image Watermarking Schemes against Salt and Pepper Noise Attack. Int. J. Bio-Sci. Bio-Technol. 7, 55–64.
Hussein, K. W., Sani, N. F. M., Mahmod, R., and Abdullah, M. T. (2013). Enhance Luhn algorithm for validation of credit cards numbers. Int. J. Comput. Sci. Mobile Computing 2, 262–272.
Johansson, R. (2015). Developing a Knock-out Code for Production Purposes. M. eng. thesis, University of Lund, Sweden.
Solomon, C., and Breckon, T. (2011). Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab. Wiley-Blackwell. doi: 10.1002/9780470689776
Arndt, J. (2010). Generating Random Permutations. PhD thesis, University of Australian National, Canberra.
Ušáková, A., Kotuliaková, J., and Zajac, M. (2002). Using of Discrete Orthogonal Transforms for Convolution. J. Electrical Eng., 53, 285–288.
Solomon, C., and Breckon, T. (2008). Elementary Number Theory. Peter and Productions, HHH.
Kaur, N., and Nagpal, R. (2014). Authenticated Diffie-Hellman Key Exchange Algorithm. Int. J. Comput. Sci. Inf. Technol. 5, 5404–5407.
Hoffstein, J., Pipher, J. C., and Silverman, J. H. (2008). An Introduction of Mathematical cryptography, 1st ed., New York: Springer.
Delfs, H., and Knebl, H. (2015). Introduction to Cryptography: Principles and Applications, New York: Springer.
Al-Husainy, M. A. (2009). Image Steganography by mapping Pixels to letters. J. Comput. Sci. 5, 33–38.
Nilizadeh, A. F., and Nilchi, A. R. N. (2013). Steganography on RGB Images Based on a “Matrix Pattern” using Random Blocks, I.J.Modern Education and Computer Science, 4, 8–18. Avalilable at: http://www.mecspress.org/
Nilizadeh, A. F., Mazurczyk, W., Zou, C. and Leavens, G. T. (2017). Information hiding in RGB images using an improved matrix pattern approach. In Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, 1407–1415.