CFP last date
20 May 2024
Reseach Article

Study of Effect of DCT Domain Steganography Techniques in Spatial Domain for JPEG Images Steganalysis

by G.R. Suryawanshi, S.N. Mali
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 127 - Number 6
Year of Publication: 2015
Authors: G.R. Suryawanshi, S.N. Mali
10.5120/ijca2015906396

G.R. Suryawanshi, S.N. Mali . Study of Effect of DCT Domain Steganography Techniques in Spatial Domain for JPEG Images Steganalysis. International Journal of Computer Applications. 127, 6 ( October 2015), 16-20. DOI=10.5120/ijca2015906396

@article{ 10.5120/ijca2015906396,
author = { G.R. Suryawanshi, S.N. Mali },
title = { Study of Effect of DCT Domain Steganography Techniques in Spatial Domain for JPEG Images Steganalysis },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 127 },
number = { 6 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 16-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume127/number6/22733-2015906396/ },
doi = { 10.5120/ijca2015906396 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:19:10.106744+05:30
%A G.R. Suryawanshi
%A S.N. Mali
%T Study of Effect of DCT Domain Steganography Techniques in Spatial Domain for JPEG Images Steganalysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 127
%N 6
%P 16-20
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Steganography is a technique of hiding secret data into digital images in different domain like frequency, spatial or wavelet. Data hiding in image change its statistical properties which leaves vulnerability for Steganalysis. In this paper a effective study is carried out for frequency domain Steganography and It’s effects in spatial domain. Study shows that secret data embedding in frequency domain reflects significant changes in spatial domain w.r.t embedding algorithm. A set of feature is identified for the analysis of covert communication through the image.

References
  1. Arooj Nissar , A.H. Mir, “Classification of steganalysis techniques: A study,” Digital Signal Processing 20 (2010) Elsevier, pp.1758–1770 ,2010.
  2. M.Chapman, G. Davida, and M. Rennhard, “A Practical and Effective Approach to Large-Scale Automated Linguistic Steganography,” Proceedings of the Information Security Conference,, pp. 156-165, October 2001
  3. Udit Budhia, Deepa Kundur, and Takis Zourntos, “Digital Video Steganalysis Exploiting Statistical Visibility in the Temporal Domain”, IEEE Transactions On Information Forensics And Security, Vol. 1, No. 4.,2006
  4. Jessica Fridrich, Member, IEEE, And Jan Kodovský, “Rich Models For Steganalysis Of Digital Images,” IEEE Transactions On Information Forensics And Security, Vol. 7, No. 3, pp no. 868-882, 2012
  5. Min Wu, Member, IEEE, and Bede Liu, Fellow, IEEE ,“Data Hiding in Image and Video:Part I—Fundamental Issues and Solutions,” IEEE Transactions on Image Processing, Vol. 12, No. 6, June 2003"
  6. Chunfang Yang, Fenlin Liu, Xiangyang Luo, and Bin Liu, “Steganalysis Frameworks of Embedding in Multiple Least-Significant Bits,” IEEE Transactions on Information Forensics and Security, Vol. 3, No. 4, December 2008
  7. Yun Cao, Xianfeng Zhao, and Dengguo Feng, “ Video Steganalysis Exploiting Motion Vector Reversion Based Features,” IEEE Signal Processing Letters, Vol 19, No. 1, pp no 35-38, 2012
  8. Mengyu Qiao, Andrew H. Sung , Qingzhong Liu, “MP3 audio steganalysis,” Information Sciences 231 Elsevier 123–134, 2013
  9. R. Sridevi, A. Damodaram and S.V.L. Narasimham, “Efficient Method of Audio Steganography by Modified LSB Algorithm and Strong Encryption Key with Enhanced Security,” Journal of Theoretical and Applied Information Technology, Vol. 5, No. 6, pp. no 768 – 771, June 2009.
  10. D. Kirovski and H. Malvar, “Spread spectrum Watermarking of Audio Signals,” IEEE Transactions on Signal Processing, vol. 51, no. 4, pp. 1020 – 1033, April 2003.
  11. Tomáš Pevný, Jessica Fridrich, And Andrew D. Ker, “From Blind To Quantitative Steganalysis,” IEEE Transactions On Information Forensics And Security, Vol. 7, No. 2, pp. no 445-454, 2012
  12. Jan Kodovský, Jessica Fridrich, “Ensemble Classifiers For Steganalysis Of Digital Media,” IEEE Transactions On Information Forensics And Security, Vol. 7, No. 2, pp no. 432-444, 2012
  13. I. Avcibas, M. Nasir, and B. Sankur., “Steganalysis Based on Image Quality Metrics,” IEEE 4th Workshop on Multimedia Signal Processing, pages 517–522, 2001
  14. K. Sullivan, U. Madhow, S. Chandrasekaran, and B. Manjunath, “Steganalysis for Markov Cover Data With Applications to Images,” IEEE Transactions on Information Forensics and Security, 1(2):275–287, 2006
  15. R. J. Anderson, “Stretching the Limits of Steganography,” 1st International Workshop on Information Hiding, 1174:39–48, 1996.
  16. R. J. Anderson and F. A. P. Petitcolas, “On the limits of Steganography,” IEEE Journal of Selected Areas in Communications, 16(4):474–481, 1998
  17. S. Badura and S. Rymaszewski, “Transform Domain Steganography in DVD Video and Audio Content,” IEEE International Workshop on Imaging Systems and Techniques, pages 1–5, 2007
  18. X.Chen, Y. Wang, T. Tan, and L. Guo, “Blind Image Steganalysis Based on Statistical Analysis of Empirical Matrix,” International Conference on Pattern Recognition, 3:1107–1110, 2006
  19. G. Xuan, Y. Q. Shi, J. Gao, D. Zou, C. Yang, Z. Zhang, P. Chai, C. Chen, and W. Chen,“Steganalysis Based onMultiple Features Formed by Statistical Moments of Wavelet Characteristic Functions,” 7th International Workshop on Information Hiding, 3727:262–277, 2005
  20. Y. Q. Shi, G. Xuan, D. Zou, J. Gao, C. Yang, Z. Zhang, P. Chai, W. Chen, and C. Chen, “Image Steganalysis Based on Moments of Characteristic Functions Using Wavelet Decomposition, Prediction-Error Image, and Neural,” Network. IEEE International Conference on Multimedia and Expo, pages 269–272, 2005
  21. C. Chen, Y. Q. Shi, W. Chen, and G. Xuan, “ Statistical Moments Based Universal Steganalysis using JPEG 2-D Array and 2-D Characteristic Function,” IEEE International Conference on Image Processing, pages 105–108, 2006
  22. H. Farid, “Detecting Steganographic Messages in Digital Images,” TR2001-412, Department of Computer Science, Dartmouth College, 2001
  23. S. Lyu and H. Farid, “Steganalysis Using Higher-Order Image Statistics,” IEEE Transactions on Information Forensics and Security, 1(1):111–119, 2006.
  24. Z. Liu, L. Ping, J. Chen, J. Wang, and X. Pan, “ Steganalysis Based on Differential Statistics,” 5th International Conference on Cryptology and Network Security, 4301:224–240, 2006
  25. J. Harmsen and W. Pearlman, “Steganalysis of Additive-Noise Modelable Information Hiding,” Proceedings of the SPIE on Security and Watermarking of Multimedia Contents V, 5020:131–142, 2003
  26. J. Fridrich, “Feature-Based Steganalysis for JPEG Images and its Implications for Future Design of Steganographic Schemes,” 6th International Workshop on Information Hiding, 3200:67–81, 2004
  27. Pritesh Pathak, s. selvakumar, “ Blind Image Steganalysis of JPEG images using feature extraction through the process if dilation,” Elsevier, Digital Investigation,1-11 2014
  28. Ji-cang Lu , Fen-lin liu, “ Selection of image features for steganalysis based on the fisher criterion,” Elsevier, Digital Investigation, 1-10,2014
  29. Xiaodan Hou, Tao Zhang,Gang et al, “ A Novel Steganalysis Framework of Heterogeneous Image Based on GMM Clustering,” Elsevier, Signal processing: Image communication,10.1016,2014
  30. Vojtech Holub and Jessica Fridrich, “Random projections of residual for digital image Steganalysis,” IEEE transaction on inforatmion forensics and security ,Vol 8 No 12 , 2013
  31. Erkan Bostanci, Nadia Kanwal and Adrian F, “ Spatial statistics of image features for performance comparison,” IEEE transaction on Image processing , Vol 23, no 1 , 2014
Index Terms

Computer Science
Information Sciences

Keywords

Steganalysis Feature Extraction Image Quality Measures (IQM).