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Perturbation Hiding and the Batch Steganography Problem

  • Andrew D. Ker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5284)

Abstract

The batch steganography problem is how best to split a steganographic payload between multiple covers. This paper makes some progress towards an information-theoretic analysis of batch steganography by describing a novel mathematical abstraction we call perturbation hiding. As well as providing a new challenge for information hiding research, it brings into focus the information asymmetry in steganalysis of multiple objects: Kerckhoffs’ Principle must be interpreted carefully.

Our main result is the solution of the perturbation hiding problem for a certain class of distributions, and the implication for batch steganographic embedding. However, numerical computations show that the result does not hold for all distributions, and we provide some additional asymptotic results to help explore the problem more widely.

Keywords

Exponential Family Natural Parameter Covert Channel Multiple Cover Distribution Family 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Ker, A.: Batch steganography and pooled steganalysis. In: Camenisch, J.L., Collberg, C.S., Johnson, N.F., Sallee, P. (eds.) IH 2006. LNCS, vol. 4437, pp. 265–281. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Ker, A.: Batch steganography and the threshold game. In: Security, Steganography and Watermarking of Multimedia Contents IX. In: Proc. SPIE, vol. 6505, pp. 0401–0413 (2007)Google Scholar
  3. 3.
    Ker, A.: Steganographic strategies for a square distortion function. In: Security, Forensics, Steganography and Watermarking of Multimedia Contents X. In: Proc. SPIE, vol. 6819 (2008)Google Scholar
  4. 4.
    Ker, A.: A capacity result for batch steganography. IEEE Signal Processing Letters 14(8), 525–528 (2007)CrossRefGoogle Scholar
  5. 5.
    Cachin, C.: An information-theoretic model for steganography. Information and Computation 192(1), 41–56 (2004)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Wang, Y., Moulin, P.: Perfectly secure steganography: Capacity, error exponents, and code constructions. IEEE Trans. Information Theory (to appear, 2008)Google Scholar
  7. 7.
    Kullback, S., Leibler, R.: On information and sufficiency. Annals of Mathematical Statistics 22, 79–86 (1951)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Kerckhoffs, A.: La cryptographie militaire. Journal des sciences militaires IX, 5–38, 161–191 (1883)Google Scholar
  9. 9.
    Cayre, F., Bas, P.: Kerckhoffs-based embedding security classes for WOA data-hiding. IEEE Trans. Information Forensics and Security (to appear, 2008)Google Scholar
  10. 10.
    Dolev, D., Yao, A.: On the security of public key protocols. IEEE Trans. Information Theory 29(2), 198–208 (1983)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Darmois, G.: Sur les lois de probabilité à estimation exhaustive. Comptes Rendus de l’Académie des Sciences 200, 1265–1266 (1935)zbMATHGoogle Scholar
  12. 12.
    Fridrich, J., Soukal, D.: Matrix embedding for large payloads. IEEE Trans. Information Forensics and Security 1(3), 390–394 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Andrew D. Ker
    • 1
  1. 1.Oxford University Computing LaboratoryOxfordEngland

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