Studi Steganografi Pada Citra Digital Menggunakan Shuffled Singular Value Decomposition (SSVD)
Stegangraphy is a technique for embed secret message in original image. It has an important role in the field of information hiding for secret communication. Many research about steganography tecniques have been developed, one of them is singular value decomposition (SVD). SVD method is popular discused in many tecnique such us steganography and watermarking. In addition to SVD there is a method which can give better result than SVD on watermaring technique that is Shuffled SVD. The differences between SSVD and SVD is in shuffle process which applied before applying SVD. The popularity of SSVD in the watermarking technique made the writer intererest to propose an image steganography tecnique using shuffled singular value decomposition (SSVD). The data used are two original RGB imaage and a message RGB image. Quality measured by PSNR and Correlation Coefficient. The experimental result show that the shuffling process on the secret message caused embedded message can’t read easyly so the secret message is more secure.
R. Bharathipriya, T. Nadu, and T. Nadu, “A Comparative Study on Secured Image Transmission Using Steganography Techniques,” Proc. UGC Spons. Natl. Conf. Adv. Netw. Appl., no. March, pp. 3–6, 2015.
S. Rajkumar and G. Malathi, “A Comparative Analysis on Image Quality Assessment for Real Time Satellite Images,” Indian J. Sci. Technol., vol. 9, no. September, 2016.
W. Luo, F. Huang, and J. Huang, “Edge Adaptive Image Steganography Based on LSB Matching Revisited,” IEEE Trans. Inf. FORENSICS Secur., vol. 5, no. 2, pp. 201–214, 2010.
Y. J. Chanu, K. M. Singh, and T. Tuithung, “A Robust Steganographic Method based on Singular Value Decomposition,” Int. J. Inf. Comput. Technol., vol. 4, no. 7, pp. 717–726, 2014.
M. Douglas, K. Bailey, M. Leeney, K. Curran, and M. Douglas, “An overview of steganography techniques applied to the protection of biometric data,” Multimed Tools Appl, pp. 17333–17373, 2018.
S. Singh, R. Singh, and T. J. Siddiqui, “Singular Value Decomposition Based Image Steganography Using Integer Wavelet Transform,” Advances in Signal Processing and Intelligent Recognition Systems, Advances in Intelligent Systems and Computing, pp. 593–594, 2016.
T. Bhuyan, V. K. Srivastava, and F. Thakkar, “Shuffled SVD based robust and secure digital image watermarking,” Int. Conf. Electr. Electron. Optim. Tech. ICEEOT 2016, pp. 1229–1233, 2016.
R. S. Run, S. J. Horng, J. L. Lai, T. W. Kao, and R. J. Chen, “An improved SVD-based watermarking technique for copyright protection,” Expert Syst. Appl., vol. 39, no. 1, pp. 673–689, 2012.
A. Rashid and M. K. Rahim, “Critical Analysis of Steganography ‘ An Art of Hidden Writing ,’” Int. J. Secur. Its Appl., vol. 10, no. 3, pp. 259–282, 2016.
N. S. Chavan, “RESEARCH ARTICLE IMAGE STEGANOGRAPHY – AN OVERVIEW,” Int. J. Recent Sci. Res., vol. 6, pp. 4800–4804, 2015.
K. Loukhaoukha, A. Refaey, K. Zebbiche, and M. Nabti, “On the Security of Robust Image Watermarking Algorithm based on Discrete Wavelet Transform , Discrete Cosine Transform and Singular Value Decomposition,” Appl. Math. Inf. Sci., vol. 1166, no. 3, pp. 1159–1166, 2015.
V. Sharma, D. Srivastava, and M. Pratistha, “A Study of Steganography Based Data Hiding Techniques,” Int. J. Emerg. Res. Manag. &Technology, vol. 9359, no. 4, pp. 145–150, 2017.
A. Cheddad, J. Condell, K. Curran, and P. M. Kevitt, “Digital Image Steganography : Survey and Analysis of Current Methods,” Signal Processing, vol. 90, no. 3, pp. 727–752, 2010.
B. Ratner, “The correlation coeffi cient : Its values range between + 1 / − 1 , or do they ?,” J. Targeting, Meas. Anal. Mark., vol. 17, pp. 139–142, 2009.
- There are currently no refbacks.
Limits: Journal Mathematics and its Aplications by Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at https://iptek.its.ac.id/index.php/limits.