Skip to main content
SpringerLink
Log in

Which gray level should be given the smallest cost for adaptive steganography?

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

Abstract

Currently, the most successful approach to steganography in digital image is distortion-minimization framework, which reduces the steganographers’ work to the design of distortion function with the aid of practical coding schemes. Previous distortion functions for spatial images are all position dependent, in which cost is determined by the relationships between neighboring pixels. Noticing that Gamma encoding is usually involved in image preprocessing in many cameras or image processing software, which causes some pixels to change greatly, we believe these pixels sensitive to Gamma encoding are more suitable for modification, because they are hard to model due to their large variations. Inspired by this idea, we proposed a position independent scheme, where the cost is only linked to the gray level. The effectiveness of our work is verified by extensive experimental results, which reveal an interesting relationship between steganographic costs and gray levels. The speed test shows that the speed of proposed scheme is very high thus suitable to be used in the real-time applications.

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

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

Similar content being viewed by others

References

  1. Alattar AM (2004) Reversible watermark using the difference expansion of a generalized integer transform. IEEE Trans Image Process 13(8):1147–1156

    Article  MathSciNet  Google Scholar 

  2. Bas P, Filler T, Pevnỳ T (2011) break our steganographic system: the ins and outs of organizing boss Information hiding. Springer, pp 59–70

  3. Bas P, Furon T (2007) Bows2-original. http://bows2.ec-lille.fr/

  4. Denemark T, Fridrich J (2015) Improving steganographic security by synchronizing the selection channel Proceedings of the 3rd ACM workshop on information hiding and multimedia security. ACM, pp 5–14

  5. Filler T, Fridrich J (2010) Gibbs construction in steganography. IEEE Trans Inf Forensic Secur 5(4):705–720

    Article  Google Scholar 

  6. Filler T, Judas J, Fridrich J (2011) Minimizing additive distortion in steganography using syndrome-trellis codes. IEEE Trans Inf Forensic Secur 6(3):920–935

    Article  Google Scholar 

  7. Fridrich J (2009) Steganography in digital media: principles, algorithms, and applications. Cambridge University Press

  8. Fridrich J, Filler T (2007) Practical methods for minimizing embedding impact in steganography Electronic imaging 2007. International Society for Optics and Photonics, pp 650,502–650,502

  9. Fridrich J, Kodovskỳ J (2012) Rich models for steganalysis of digital images. IEEE Trans Inf Forensic Secur 7(3):868–882

    Article  Google Scholar 

  10. Fridrich J, Kodovskỳ J (2013) Multivariate gaussian model for designing additive distortion for steganography ICASSP, pp 2949–2953

    Google Scholar 

  11. Guo L, Ni J, Shi YQ (2012) An efficient jpeg steganographic scheme using uniform embedding 2012 IEEE international workshop on information forensics and security (WIFS). IEEE, pp 169–174

  12. Holub V, Fridrich J (2012) Designing steganographic distortion using directional filters 2012 IEEE international workshop on information forensics and security (WIFS). IEEE, pp 234–239

  13. Holub V, Fridrich J (2013) Digital image steganography using universal distortion Proceedings of the first ACM workshop on information hiding and multimedia security. ACM, pp 59–68

  14. Huang F, Huang J, Shi YQ (2012) New channel selection rule for jpeg steganography. IEEE Trans Inf Forensic Secur 7(4):1181–1191

    Article  Google Scholar 

  15. Kodovskỳ J, Fridrich J, Holub V (2012) Ensemble classifiers for steganalysis of digital media. IEEE Trans Inf Forensic Secur 7(2):432–444

    Article  Google Scholar 

  16. Kodovskỳ J, Pevnỳ T, Fridrich J (2010) Modern steganalysis can detect yass IS&T/SPIE electronic imaging. International Society for Optics and Photonics, pp 754,102–754,102

  17. Li B, He J, Huang J, Shi YQ (2011) A survey on image steganography and steganalysis. J Inf Hiding Multimed Signal Process 2(2):142–172

    Google Scholar 

  18. Li B, Tan S, Wang M, Huang J (2014) Investigation on cost assignment in spatial image steganography. IEEE Trans Inf Forensic Secur 9(8):1264–1277

    Article  Google Scholar 

  19. Li B, Wang M, Huang J, Li X (2014) A new cost function for spatial image steganography 2014 IEEE international conference on image processing (ICIP). IEEE, pp 4206–4210

  20. Li B, Wang M, Li X, Tan S, Huang J (2015) A strategy of clustering modification directions in spatial image steganography. IEEE Trans Inf Forensic Secur 10(9):1905–1917

    Article  Google Scholar 

  21. Ni Z, Shi YQ, Ansari N, Su W (2006) Reversible data hiding. IEEE Trans Circ Syst Video Technol 16(3):354–362

    Article  Google Scholar 

  22. Pevnỳ T, Bas P, Fridrich J (2010) Steganalysis by subtractive pixel adjacency matrix. IEEE Trans Inf Forensic Secur 5(2):215–224

    Article  Google Scholar 

  23. Pevnỳ T, Filler T, Bas P (2010) Using high-dimensional image models to perform highly undetectable steganography Information hiding. Springer, pp 161–177

  24. Pevnỳ T, Fridrich J (2008) Benchmarking for steganography Information hiding. Springer, pp 251–267

  25. Poynton CA (1998) Rehabilitation of gamma Photonics west’98 electronic imaging. International Society for Optics and Photonics, pp 232–249

  26. Qin C, Chang CC, Hsu TJ (2015) Reversible data hiding scheme based on exploiting modification direction with two steganographic images. Multimed Tools Appl 74(15):5861–5872

    Article  Google Scholar 

  27. Qin C, Hu YC (2016) Reversible data hiding in vq index table with lossless coding and adaptive switching mechanism. Signal Process 129:48–55

    Article  Google Scholar 

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

    Article  Google Scholar 

  29. Sedighi V, Fridrich J, Cogranne R (2015) Content-adaptive pentary steganography using the multivariate generalized gaussian cover model IS&T/SPIE electronic imaging. International Society for Optics and Photonics, pp 94,090H–94,090H

  30. Thodi DM, Rodríguez JJ (2007) Expansion embedding techniques for reversible watermarking. IEEE Trans Image Process 16(3):721–730

    Article  MathSciNet  Google Scholar 

  31. Tian J (2003) Reversible data embedding using a difference expansion. IEEE Trans Circ Systems Video Technol 13(8):890–896

    Article  Google Scholar 

  32. Zhang W, Zhang Z, Zhang L, Li H, Yu N (2016) Decomposing joint distortion for adaptive steganography. IEEE Transactions on Circuits and Systems for Video Technology

Download references

Acknowledgements

This work was supported in part by the Natural Science Foundation of China under Grant U1636201, 61572452.

Author information

Authors and Affiliations

  1. University of Science and Technology of China, Anhui, China

    Yao Wei, Weiming Zhang, Weihai Li, Nenghai Yu & Xi Sun

  2. Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Anhui, China

    Yao Wei, Weihai Li, Nenghai Yu & Xi Sun

Authors
  1. Yao Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Weiming Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weihai Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nenghai Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xi Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Weiming Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wei, Y., Zhang, W., Li, W. et al. Which gray level should be given the smallest cost for adaptive steganography?. Multimed Tools Appl 77, 17861–17874 (2018). https://doi.org/10.1007/s11042-017-4565-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-017-4565-5

Keywords

Search

Navigation