Improving side-informed JPEG steganography using two-dimensional decomposition embedding method | Multimedia Tools and Applications Skip to main content
Log in

Improving side-informed JPEG steganography using two-dimensional decomposition embedding method

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Side-informed JPEG steganography is a renowned technology of concealing information for the high resistance to blind detection. The existed popular side-informed JPEG steganographic algorithms use binary embedding method with the corresponding binary distortion function. Then, the embedding methods and binary distortion functions of popular side-informed JPEG steganographic algorithms are analyzed and the wasted secure capacity by using the binary embedding operation is pointed out. Thus, the detection resistance of the side-informed JPEG steganographic algorithms can be improved if the embedding operation is changed to ternary mode which causes less changes than binary embedding at same payload. The problem of using ternary embedding is to define a suitable ternary distortion function. To solve this, a two-dimensional decomposition embedding method is proposed in this paper. The proposed ternary distortion function is defined by transforming the problem into two different binary distortion functions of two layers that based on the ternary entropy decomposition. Meanwhile, the proposed method ensures the minimal value of the distortion function on each layer can be reached in theory. Several popular side-inform JPEG steganographic algorithms (NPQ, EBS, and SI-UNIWARD) are improved through defining ternary distortion function by the proposed method. The experimental results on parameters, blind detection and processing time show that the proposed method increases the blind detection resistance of side-informed steganographic algorithm with acceptable computation complexity.

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

Access this article

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. It is easy to extend the steganographic algorithms of grayscale image to color image if considering the three channels of color image is independent to each other, and the databases of the side-informed JPEG steganographic algorithms NPQ, EBS and UNIWARD are grayscale images. Thus, this paper focuses on the grayscale images, and the well-known database BOSSbase ver. 1.01 is used in the experiments.

  2. Proposed by Patrick Bas, Tomas Filler, Tomas Pevny in ICASSP 2013, contains 10,000 512 × 512 grayscale images, available: http://agents.fel.cvut.cz/stegodata/

  3. Actually, the value of T can also be changed in the CC method, but this will significantly increase the number of the candidate images, and the experimental results showed in the Fig. 5 implies that the effect of T-value stay steady in [0.1, 0.3], thus, the CC method just changes the values of β.

References

  1. Cover TM, Thomas JA (2012) Elements of information theory. John Wiley & Sons Press, Hoboken

    MATH  Google Scholar 

  2. Crandall R (1998) Some Notes on Steganography. Steganography Mailing List. http://os.inf.tu-dresden.de/west-feld/crandall.pdf

  3. Filler T, Fridrich J (2010) Minimizing Additive Distortion Functions with Non-binary Embedding Operation in Steganography. In: Proc of the 2th IEEE International Workshop on Information Forensics and Security, IEEE, Seattle, 1–6

  4. Filler T, Fridrich J (2011) Design of Adaptive Steganographic Schemes for Digital Images. In: Proc. of the 13th IS&T/SPIE Electronic Imaging, Media Watermarking, Security, and Forensics, vol. 7880, no. 0F, 1–14

  5. Filler T, Ker AD, Fridrich J (2009) The Square Root Law of Steganographic Capacity for Markov Covers. In: Proc. of the 11th. IS&T/SPIE Electronic Imaging, Media Forensics and Security 7254(08):1–11

    Google Scholar 

  6. Filler T, Judas J, Fridrich J (2010) Minimizing Embedding Impact in Steganography Using Trellis-coded Quantization. In: Proc. of the 12th IS&T/SPIE Electronic Imaging, Media Forensics and Security, vol. 7541, no. 05, 1–14

  7. Fridrich J (2009) Steganography in Digital Media: Principles, Algorithms, and Applications. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  8. Fridrich J, Filler T (2007) Practical Methods for Minimizing Embedding Impact in Steganography. In: Proc. of the 9th IS&T/SPIE Electronic Imaging, Photonics West, vol. 6505, no. 02, 01–15

  9. Fridrich J, Goljan M, Soukal D (2004) Perturbed Quantization Steganography with Wet Paper Codes. In: Proc. of the 6th ACM Workshop on Multimedia & Security, 4–15, ACM, New York

  10. Fridrich J, Goljan M, Lisonek P, Soukal D (2005) Writing on wet paper. IEEE Trans Signal Process 53(10):3923–3935

    Article  MathSciNet  Google Scholar 

  11. Fridrich J, Pevny T, Kodovshy J (2007) Statistically Undetectable Jpeg Steganography: Dead Ends Challenges, and Opportunities. In: Proc. of the 9th ACM Workshop on Multimedia & Security, ACM, New York, 3–14

  12. Guo L, Ni J, and Shi YQ (2012) An Efficient Jpeg Steganographic Scheme Using Uniform Embedding. In: Proc of the 4th IEEE International Workshop on Information Forensics and Security, 169–174, IEEE, Tenerife

  13. Holub V, Fridrich J (2015) Low-complexity features for jpeg steganalysis using Undecimated DCT. IEEE Trans. Inf. Forensics Secur. 10(2):219–228

    Article  Google Scholar 

  14. Holub V, Fridrich J, Denemark T (2014) Universal distortion function for steganography in an arbitrary domain. EURASIP J Inf Secur 2014(1):1–13

    Article  Google Scholar 

  15. Huang J, Shi YQ (2002) Reliable information bit hiding. IEEE transactions on circuits and Systems for Video. Technology 12(10):916–920

    Google Scholar 

  16. Huang F, Huang J, Shi YQ (2012) New Channel selection rule for jpeg steganography. IEEE Transactions on Information Forensics and Security, vol. 7, no. 4, 1181–1191

  17. Ker AD (2007). A Fusion of Maximum Likelihood and Structural Steganalysis. In: Proc of the 9th International Workshop on Information Hiding, 4567, 204–219

  18. Ker AD, Pevny T, Kodovsky J, Fridrich J (2008) The Square Root Law of Steganographic Capacity. In: Proc. of the 10th ACM Workshop on Multimedia & Security, ACM, New York, 107–116

  19. Ker AD, Bas P, Böhme R, Cogranne R, Craver S, Filler T, Fridrich J, Pevny T (2013) Moving Steganography and Steganalysis from the Laboratory into the Real World. In: Proc of the first ACM Workshop on Information Hiding and Multimedia Security, ACM, New York, 45-58

  20. Kim Y, Duric Z, Richards D (2007) Modified Matrix Encoding Technique for Minimal Distortion Steganography. In: Proc of the 9th International Workshop on Information Hiding, 4437, 314-327

  21. Kodovsky J, Fridrich J (2009) Calibration revisited. In: Proc. of the 11th ACM Workshop on Multimedia & Security, ACM, New York, 63-74

  22. Kodovsky J, Fridrich J (2012) Steganalysis of Jpeg Images Using Rich Models. In: Proc. of the 14th IS&T/SPIE Electronic Imaging, Media Watermarking, Security, and Forensics, vol. 8303, no. 0 A, 01–13

  23. Kodovsky J, Pevny T, Fridrich J (2010) Modern Steganalysis can Detect YASS. In: Proc. of the 12th IS&T/SPIE Electronic Imaging,. Media Forensic Secur 7541(02):1–11

    Google Scholar 

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

    Article  Google Scholar 

  25. Kullback S (1968) Information Theory and Statistics. Courier Corporation Press, Mineola

    MATH  Google Scholar 

  26. Lin CC, Liu XL, Tai WL, et al. (2013) A novel reversible data hiding scheme based on AMBTC compression technique. Multimed Tool Appl 74(11):1–20

    Google Scholar 

  27. Lin CC, Liu XL, Yuan SM (2015) Reversible data hiding for VQ-compressed images based on search-order coding and state-codebook mapping. Inf Sci 293:314–326

    Article  Google Scholar 

  28. Liu Q (2011) Steganalysis of DCT-embedding based adaptive steganography and YASS. In: Proc. of the 13th ACM Workshop on Multimedia & Security. ACM, New York 2011;77-86

  29. Luo W, Huang F, Huang J (2010) Edge adaptive image steganography based on lsb matching revisited. IEEE Trans Inf Forensics Secur 5(2):201–2014

    Article  Google Scholar 

  30. Muhammad K, Sajjad M, Mehmood I, et al. (2015) A Novel Magic LSB Substitution Method (M-LSB-SM) Using Multi-level Encryption and Achromatic Component of An Image. Multimed Tool Appl 93(5):1–27

    Google Scholar 

  31. Provos N (2001) Defending against statistical steganalysis. In: Proc of Usenix Security Symposium, vol. 10, 323–336

  32. Sedighi V, Fridrich J, Cogranne R (2015) Content-Adaptive Pentary Steganography Using the Multivariate Generalized Gaussian Cover Model. In: Proc of the SPIE - The International Society for Optical Engineering, vol 9409, no 94090H, 1–13

  33. Sedighi V, Cogranne R, Fridrich J (2016) Content-adaptive steganography by minimizing statistical detectability[J. IEEE Trans Inf Forensics Secur 11(2):221–234

    Article  Google Scholar 

  34. Wang C, Ni J (2012) An Efficient Jpeg Steganographic Scheme Based on the Block Entropy of DCT Coefficients. In: Proc of the 37th IEEE International Conference on Acoustics, Speech and Signal Processing, 1785–1788, IEEE, Kyoto

  35. Yang Y, Zhang W, Liang D, et al. (2016) Reversible data hiding in medical images with enhanced contrast in texture area. Digital Signal Process, 2016 52(C):13–24

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 61379151, 61272489, 61572452 and 61572052), the National Natural Science Youth Foundation of China (No. 61302159, 61401512), the Excellent Youth Foundation of Henan Province of China (No. 144100510001), and the Foundation of Science and Technology on Information Assurance Laboratory (No. KJ-14-108).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiangyang Luo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bao, Z., Luo, X., Zhang, W. et al. Improving side-informed JPEG steganography using two-dimensional decomposition embedding method. Multimed Tools Appl 76, 14345–14374 (2017). https://doi.org/10.1007/s11042-016-3823-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-016-3823-2

Keywords

Navigation