4LSB BASED DATA HIDING IN COMPLEX REGION OF DIGITAL IMAGES AND ITS EFFECTS ON EDGES AND HISTOGRAM

  • Nasir Ahmad Department of Electronic and Electrical Engineering, Loughborough University, UK
Keywords: Steganography, Edge, Canny edge detection, Histogram difference, Steganalysis

Abstract

Data hiding in the complex regions of cover image make the use of edges for hiding and communicating secret
information. The complex region in a digital image is the least sensitive to human visual system (HVS) in term of
changes than smooth region. The data hiding in the complex regions affect the edges and the histogram of the image.
These two may cause the existence of hidden information to be detected. In this paper, the effect on image edges
and histogram is investigated when subjected to true edge based 4 least significant bits (4LSB) steganography. The
true edge based 4LSB steganography technique has been found very efficient, creating no significant effect on edges
and undetectable histogram differences. Which prove this technique immune to histogram difference steganalysis. The
quality of the edges is preserved and a PNSR of greater than 74dB has been observed for different cover images
for the true edge based 4LSB steganography. The quality of stego images, edges can been observed qualitatively
and it be seen clearly that no significant changes are introduced due to hiding information in edges using the true
edge based steganography.

References

1. Johnson, N. F., and Jajodia, S., (1998), “Exploring
steganography: Seeing the unseen,” Computer, vol.
31, no. 2, pp. 26-34.
2. Khan, S., Ahmad, N., Ismail, M., Minallah, N.,
and Khan, T., (2015), “A secure true edge based 4
least significant bits steganography,” International
Conference on Emerging Technologies (ICET),
Peshawar, Pakistan, pp.1-4.
3. Ma, B., and Shi, Y. Q., (2016), “A reversible data
hiding scheme based on code division multiplexing,”
IEEE Transactions on Information Forensics and
Security, vol. 11, no. 9, pp.1914-1927.
4. Honsinger, C. W., Jones, P. W., Rabbani, M., and
Stoffel, J. C. (2001), “Lossless recovery of an original
image containing embedded data,” Washington,
DC: U.S. Patent and Trademark Office, 6 (278&791),
issued August 21, 2001.
5. Khan, S., and Yousaf, M. H., (2013), “Implementation
of VLSB Stegnography Using Modular Distance
Technique,” Innovations and Advances in Computer,
Information, Systems Sciences, and Engineering,
Springer New York, pp. 511-525.
6. Irfan, M. A., Ahmad, N., and Khan, S., (2014),
“Analysis of Varying Least Significant Bits DCTand Spatial Domain Stegnography,” Sindh Univ.
Res. Jour. (Sci. Ser.), vol. 46, no. 3, pp. 301-306.
7. Macq, B., and Dewey, F., (1999), “Trusted headers
for medical images,” DFG VIII-D II Watermarking
Workshop, Germany: Erlangen, vol. 10, pp.12-20.
8. Vleeschouwer, C. D., Delaigle, J. F., and Macq, B.,
(2001), “Circular interpretation of histogram for
reversible watermarking,” IEEE 4th Workshop on
Multimedia Signal Processing, pp. 345-350.
9. Goljan, M., Fridrich, J., and Du, R., (2001),
“Distortion-free data embedding for images,”
Information Hiding, Springer Berlin Heidelberg,
pp. 27-41.
10. Khan, S., Khan, M. N., Iqbal, S., Shah, S. Y., and
Ahmad, N., (2013), “Implementation of Variable Tone
Variable Bits Gray-Scale Image Stegnography Using
Discrete Cosine Transform,” Journal of Signal and
Information Processing, vol. 4, no. 4, pp. 343-350.
11. Xuan, G., Zhu, J., Chen, J., Shi, Y. Q., Ni, Z., and
Su, W., (2002) “Distortionless data hiding based on
integer wavelet transform,” Electronics Letters, vol.
38, no. 25, pp. 1646-1648.
12. Liu, C., Hoi, S. C., Zhao, P., Sun, J., and Lim, E.
P., (2016) “Online Adaptive Passive-Aggressive
Methods for Non-Negative Matrix Factorization
and Its Applications” 25th ACM International
on Conference on Information and Knowledge
Management, pp. 1161-1170.
13. Guan, N., Tao, D., Luo, Z., and Yuan, B., (2012),
“NeNMF: an optimal gradient method for nonnegative
matrix factorization,” IEEE Transactions on
Signal Processing, vol. 60, no. 6, pp. 2882-2898.
14. Hong, W., and Chen, T. S., (2012), “A novel data
embedding method using adaptive pixel pair matching,”
IEEE Transactions on Information Forensics
and Security, vol. 7, no. 1, pp. 176-184.
15. Hong, W., Chen, T. S., and Shiu, C. W., (2009),
“Reversible data hiding for high quality images
using modification of prediction errors,” Journal of
Systems and Software, vol. 82, no. 11, pp. 1833-1842.
16. Hong, W., Chen, T. S., and Shiu, C. W., (208), “A
minimal Euclidean distance searching technique
for Sudoku steganography,” IEEE International
Symposium on Information Science and Engineering
(ISISE’08), vol. 1, pp. 515-518.
17. Khan, S., Ismail, M., Khan, T., and Ahmad, N. (2016),
“Enhanced stego block chaining (ESBC) for low
bandwidth channel”, Security and Communication
Networks, vol. 9, no. 18, pp. 6239-6247.
18. Jung, K. Y., and Yoo, K. Y., (2014), “Data hiding
using edge detector for scalable images,” Multimedia
tools and applications, vol. 71, no. 3, pp. 1455-1468.
19. Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli,
E. P., (2004), “Image quality assessment: from error
visibility to structural similarity,” IEEE transactions
on image processing, vol. 13, no. 4, pp.600-612.
20. Khan, S., Ahmad, N., and Wahid, M., (2016) “Varying
index varying bits substitution algorithm for the
implementation of VLSB steganography”, Journal
of the Chinese Institute of Engineers, vol. 39, no.
1, pp. 101-109.
21. SIPI, USC, (2016) “The USC-SIPI Image
Database” http://sipi.usc.edu/services/database/
data-base.html.
Published
2017-11-20