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Embedding Strategy for Batch Adaptive Steganography

  • Zengzhen ZhaoEmail author
  • Qingxiao Guan
  • Xianfeng Zhao
  • Haibo Yu
  • Changjun Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10082)

Abstract

In this paper, we present a new embedding strategy for batch adaptive steganography. This strategy can make up for the problem when applying batch steganography to adaptive steganography and determine the sub-batch of cover images to carry the total message. Firstly, we define a secure factor \(\alpha \) to evaluate the embedding security. Then, we utilize the secure factor \(\alpha \) to calculate the corresponding payloads for each image based on distortion-limited sender (maximizing the payload while introducing a fixed total distortion) and fit the relation curve for the secure factor and the corresponding payload. When embedding, the images with large size and more upward convex relation curve are employed to carry the total message. Experimental results show that fitting curves vary according to images and employing images with more upward convex relation curve to carry the total message can improve the secure performance effectively.

Keywords

Steganography Security Distortion function 

Notes

Acknowledgments

This work was supported by the NSFC under U1536105 and 61303259, National Key Technology R&D Program under 2014BAH41B01, Strategic Priority Research Program of CAS under XDA06030600, and Key Project of Institute of Information Engineering, CAS, under Y5Z0131201.

References

  1. 1.
    Fridrich, J., Kodovsky, J.: Rich models for steganalysis of digital images. IEEE Trans. Inf. Forensics Secur. 7(3), 868–882 (2011)CrossRefGoogle Scholar
  2. 2.
    Denemark, T., Sedighi, V., Holub, V., Cogranne, R., Fridrich, J.: Selection-channel-aware rich model for steganalysis of digital images. In: IEEE International Workshop on Information Forensics and Security (WIFS), pp. 48–53. IEEE (2014)Google Scholar
  3. 3.
    Holub, V., Fridrich, J.: Random projections of residuals for digital image steganalysis. IEEE Trans. Inf. Forensics Secur. 8(12), 1996–2006 (2013)CrossRefGoogle Scholar
  4. 4.
    Holub, V., Fridrich, J.: Low complexity features for JPEG steganalysis using undecimated DCT. IEEE Trans. Inf. Forensics Secur. 10(2), 219–228 (2015)CrossRefGoogle Scholar
  5. 5.
    Pevný, T., Filler, T., Bas, P.: Using high-dimensional image models to perform highly undetectable steganography. In: Böhme, R., Fong, P.W.L., Safavi-Naini, R. (eds.) IH 2010. LNCS, vol. 6387, pp. 161–177. Springer, Heidelberg (2010). doi: 10.1007/978-3-642-16435-4_13 CrossRefGoogle Scholar
  6. 6.
    Holub, V., Fridrich, J.: Designing steganographic distortion using directional filters. In: IEEE International Workshop on Information Forensics and Security (WIFS), pp. 234–239. IEEE (2012)Google Scholar
  7. 7.
    Holub, V., Fridrich, J., Denemark, T.: Universal distortion design for steganography in an arbitrary domain. EURASIP J. Inf. Secur. 2014(1), 1–13 (2014)CrossRefGoogle Scholar
  8. 8.
    Li, B., Wang, M., Huang, J.: A new cost function for spatial image steganography. In: 2014 IEEE International Conference on Image Processing, pp. 4206–4210. IEEE (2014)Google Scholar
  9. 9.
    Fridrich, J., Goljan, M., Lisonek, P., Soukal, D.: Writing on wet paper. IEEE Trans. Sig. Process. 53(10), 3923–3935 (2015)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Filler, T., Judas, J., Fridrich, J.: Minimizing additive distortion in steganography using syndrome-trellis codes. IEEE Trans. Inf. Forensics Secur. 6(3), 920–935 (2011)CrossRefGoogle Scholar
  11. 11.
    Zhao, Z., Guan, Q., Zhao, X.: Constructing near-optimal double-layered syndrome-trellis codes for spatial steganography. In: 2016 ACM Workshop on Information Hiding and MultiMedia Security, pp. 139–148 (2016)Google Scholar
  12. 12.
    Ker, A., Pevný, T.: Batch steganography in the real world. In: ACM Proceedings of the on Multimedia and Security, pp. 1–10 (2012)Google Scholar
  13. 13.
    Kodovský, J., Fridrich, J., Holub, V.: Ensemble classifiers for steganalysis of digital media. IEEE Trans. Inf. Forensics Secur. 7(2), 432–444 (2012)CrossRefGoogle Scholar
  14. 14.
    Bas, P., Filler, T., Pevný, T.: “Break our steganographic system”: the ins and outs of organizing BOSS. In: Filler, T., Pevný, T., Craver, S., Ker, A. (eds.) IH 2011. LNCS, vol. 6958, pp. 59–70. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-24178-9_5 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Zengzhen Zhao
    • 1
    • 2
    Email author
  • Qingxiao Guan
    • 1
    • 2
  • Xianfeng Zhao
    • 1
    • 2
  • Haibo Yu
    • 1
    • 2
  • Changjun Liu
    • 1
    • 2
  1. 1.State Key Laboratory of Information Security, Institute of Information EngineeringChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

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