Skip to main content
SpringerLink
Log in

A method to estimate the steganographic capacity in DCT domain based on MCUU model

  • Computer Science
  • Published:
Wuhan University Journal of Natural Sciences

Abstract

In order to estimate maximum steganographic capacity of discrete cosine transform (DCT) domain in JPEG image, this paper presents a method based on the maximize capacity under undetectable model (MCUU). We analyze the relation between steganographic capacity and affecting factors (image size, steganography operator, loading band, embedding intensity and image complexity). Then we design a steganography analyzer architecture and a steganographic algorithm which can dynamically increase the steganographic capacity. Compared with other methods of embedding capacity estimation in DCT domain, the proposed methods utilizes general steganalysis methods rather than one specific steganalysis technique and takes five essential factors into account, which improves the commonality and comprehensiveness of capacity estimation, respectively. The experimental results show that steganographic capacity for quantization index modulation (QIM) is almost twice that of spread spectrum (SS) based on MCUU model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Zheng P, Wang W, Zhao B, et al. Hiding information in MPEG sequences by using of B-Frames [J]. Wuhan University Journal of Natural Sciences, 2012, 3(3): 238–242.

    Article  Google Scholar 

  2. Tang S, Jiang Y, Zhang L, et al. Audio steganography with AES for real-time covert voice over internet protocol communications [J]. Science China Information Sciences, 2014, 57(3): 1–14.

    Google Scholar 

  3. Sajedi H, Jamzad M. Secure steganography based on embedding capacity [J]. International Journal of Information Security, 2009, 8(6): 433–445.

    Article  Google Scholar 

  4. Kodovsky J, Fridrich J, Holub V. Ensemble classifier for steganalysis of digital media [J]. IEEE Transactions on Information Forensics and Security, 2012, 7(2): 432–444.

    Article  Google Scholar 

  5. Li S, Zhang X, Wang S. Study of digital image steganography method based on tolerable distortion range [J]. Journal of Image and Graphics, 2007, 12(2): 212–217(Ch).

    Google Scholar 

  6. Mao J F, Niu X X, Yang Y X, et al. JPEG2000 image maximum steganography payload based on MPUI model [J]. Journal of Software, 2014, 7: 1606–1620(Ch).

    Google Scholar 

  7. Rainer B, Christian K. A steganographic scheme for secure communications based on the chaos and the euler theorem [J]. IEEE Transactions on Multimedia, 2007, 9(6): 1325–1329.

    Article  Google Scholar 

  8. Panyavaraporn J, Horkaew P, Wongtrairat W. QR Code watermarking algorithm based on wavelet transform [J]. IEEE International Symposium on Communications and Information Technologies, 2013, 13(3): 791–796.

    Google Scholar 

  9. Moulin P, O’Sullivan J A. Information-theoretic analysis of information hiding [J]. IEEE Transactions on Information Theory, 2003, 49(3): 564–593.

    Article  Google Scholar 

  10. Somekeh-Baruch A, Merhav N. On the capacity game of public watermarking system [J]. IEEE Transactions on Information Theory, 2004, 50(3): 511–524.

    Article  Google Scholar 

  11. Cohen A S, Lapidoth A. The capacity of the vector Gaussian watermarking Game [C] // Proceeding of International Symposium on Information Theory. Washington D C: IEEE Computer Society, 2001:5.

    Google Scholar 

  12. Cohen A, Lapidoth A. The Gaussian watermarking game [J]. IEEE Transactions on Information Theory, 2002, 48(6): 1639–1667.

    Article  Google Scholar 

  13. Iyer R, Borse R, Chaudhuri S. Embedding capacity estimation of reversible watermarking schemes [J]. Sadhana-Academy Proceedings in Engineering Sciences, 2014, 39(6): 1357–1385.

    Google Scholar 

  14. Chen J Y, Zhu Y F, Zhang W M, et al. Extracting attack to DCT domain sequential LSB steganography [J]. Pattern Recognition and Artificial Intelligence, 2011, 24(4): 484–491(Ch).

    CAS  Google Scholar 

  15. Chen C, Shi Y Q, Chen W, et al. Statistical moments based universal steganalysis using JPEG-2D array and 2-D characteristic function [C] // Image Processing, 2006 IEEE International Conference on. Atlanta: IEEE Computer Society, 2006: 105–108.

    Chapter  Google Scholar 

  16. Westfeld A. F5-A steganographic algorithm: High capacity despite better steganalysis [J]. Proceedings of Information Hiding Workshop, 2001, 21(37): 289–302.

    Article  Google Scholar 

  17. Dong X Z, Zhang R, Niu X X. A steganalysis algorithm on MB steganography [J]. Journal of Beijing University of Posts and Telecommunications, 2012, 35(2): 99–103(Ch).

    Google Scholar 

  18. Lu J, Liu F, Luo X Y, et al. Recognition of PQ stego images based on identifiable statistical feature [J]. Journal on Communications, 2015, 36(3): 201–210.

    Google Scholar 

  19. Solanki K, Sarkar A, Manjunath B S. YASS: Yet another steganographic scheme that resists blind steganalysis [J]. Lecture Notes in Computer Science, 2007, 4567: 16–31.

    Article  Google Scholar 

  20. Anitha M P T, Rajaram M. Overview of detecting stego-content in corporate emails: A Web-based steganalysis[J]. International Journal of Computer & Network Security, 2010, 2(9): 122–125.

    Google Scholar 

  21. Kodovsky J, Fridrich J. Quantitative structural steganalysis of Jsteg [J]. Information Forensics & Security IEEE Transactions, 2010, 5(4): 681–693.

    Article  Google Scholar 

  22. Lie W N, Lin G S. A feature-based classification technique for blind image steganalysis [J]. IEEE Transactions on Multimedia, 2005, 7(6): 1007–1020.

    Article  Google Scholar 

  23. Huang W, Zhao X F, Feng D G, et al. JPEG steganalysis based on feature fusion by principal component analysis[J]. Journal of Software, 2012, 23(7): 1869–1879(Ch).

    Article  CAS  Google Scholar 

  24. Shi Y Q, Chen C, Chen W. A Markov process based approach to effective attacking JPEG steganography [C] //Proceedings of the 8th Information Hiding Workshop. Berlin: Springer-Verlag, 2007: 249–264.

    Chapter  Google Scholar 

  25. Davidson J, Jalan J. Steganalysis using partially ordered Markov models [C] // Proceedings of the 12th Int’l Workshop on Information Hiding (IH 2010). Berlin: Springer-Verlag, 2010: 143–157.

    Google Scholar 

  26. Pevn T, Fridrich J. Merging markov and DCT features for multi-class JPEG steganalysis [C] // Proceedings of Society of Photo-Optical Instrumentation Engineers. San Jose: SPIE Proceedings, 2007, 6505(3): 28–40.

    Google Scholar 

  27. Fridrich J. Information Hiding [M. Berlin: Springer-Verlag, 2004.

    Google Scholar 

  28. Briassouli A, Tsakalides P, Stouraitis A. Hidden messages in heavy-tails: DCT-domain watermark detection using alphastable models [J]. IEEE Transactions on Multimedia, 2005, 7(4): 700–715.

    Article  Google Scholar 

  29. Jamzad M, Yaghmaee F. Achieving higher stability in watermarking according to image complexity [J]. Scientia Iranica, 2006, 13(4): 404–412.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310023, Zhejiang, China

    Jiafa Mao, Yanhong Huang, Gang Xiao, Linan Zhu & Weiguo Sheng

  2. Information Security Center, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Jiafa Mao & Xinxin Niu

Authors
  1. Jiafa Mao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yanhong Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xinxin Niu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gang Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Linan Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Weiguo Sheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jiafa Mao.

Additional information

Foundation item: Supported by the National Natural Science Foundation of China (61170271, 61170272, 61272310, 61373131, 61573316), and Zhejiang Provincial Natural Science Foundation of China (LY15F020032, LQ12 F02016, LQ15E050006)

Biography: MAO Jiafa, male, Ph.D., Associate professor, research direction: information hiding, image processing, pattern recognition, computer vision, and video fingerprint.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mao, J., Huang, Y., Niu, X. et al. A method to estimate the steganographic capacity in DCT domain based on MCUU model. Wuhan Univ. J. Nat. Sci. 21, 283–290 (2016). https://doi.org/10.1007/s11859-016-1172-7

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11859-016-1172-7

Keywords

CLC number

Search

Navigation