Advertisement

Using High-Dimensional Image Models to Perform Highly Undetectable Steganography

  • Tomáš Pevný
  • Tomáš Filler
  • Patrick Bas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6387)

Abstract

This paper presents a complete methodology for designing practical and highly-undetectable stegosystems for real digital media. The main design principle is to minimize a suitably-defined distortion by means of efficient coding algorithm. The distortion is defined as a weighted difference of extended state-of-the-art feature vectors already used in steganalysis. This allows us to “preserve” the model used by steganalyst and thus be undetectable even for large payloads. This framework can be efficiently implemented even when the dimensionality of the feature set used by the embedder is larger than 107. The high dimensional model is necessary to avoid known security weaknesses. Although high-dimensional models might be problem in steganalysis, we explain, why they are acceptable in steganography. As an example, we introduce HUGO, a new embedding algorithm for spatial-domain digital images and we contrast its performance with LSB matching. On the BOWS2 image database and in contrast with LSB matching, HUGO allows the embedder to hide 7× longer message with the same level of security level.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Anderson, R.: Stretching the limits of steganography. In: Anderson, R. (ed.) IH 1996. LNCS, vol. 1174, pp. 39–48. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  2. 2.
    Cachin, C.: An information-theoretic model for steganography. In: Aucsmith, D. (ed.) IH 1998. LNCS, vol. 1525, pp. 306–318. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  3. 3.
    Cancelli, G., Barni, M., Menegaz, G.: Mpsteg: hiding a message in the matching pursuit domain. In: Proceedings SPIE, EI, Security, Steganography, and Watermarking of Multimedia Contents VIII, San Jose, CA, vol. 6072, p. 60720P (2006)Google Scholar
  4. 4.
    Crandall, R.: Some notes on steganography. Steganography Mailing List (1998), http://os.inf.tu-dresden.de/~westfeld/crandall.pdf
  5. 5.
    Filler, T., Fridrich, J.: Fisher information determines capacity of ε-secure steganography. In: Katzenbeisser, S., Sadeghi, A.-R. (eds.) IH 2009. LNCS, vol. 5806, pp. 31–47. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  6. 6.
    Filler, T., Fridrich, J., Judas, J.: Minimizing embedding impact in steganography using Trellis-Coded Quantization. In: Proceedings SPIE, EI, Media Forensics and Security XII, San Jose, CA, January 18-20, p. 05-1–05-14 (2010)Google Scholar
  7. 7.
    Filler, T., Ker, A.D., Fridrich, J.: The Square Root Law of steganographic capacity for Markov covers. In: Proceedings SPIE, EI, Security and Forensics of Multimedia XI, San Jose, CA, January 18-21, vol. 7254, p. 08-1–08-11 (2009)Google Scholar
  8. 8.
    Franz, E.: Steganography preserving statistical properties. In: Petitcolas, F.A.P. (ed.) IH 2002. LNCS, vol. 2578, pp. 278–294. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  9. 9.
    Franz, E., Rönisch, S., Bartel, R.: Improved embedding based on a set of cover images. In: Proceedings of the 11th ACM Multimedia & Security Workshop, Princeton, NJ, September 7-8, pp. 141–150 (2009)Google Scholar
  10. 10.
    Fridrich, J.: Steganography in Digital Media: Principles, Algorithms, and Applications. Cambridge University Press, Cambridge (2009)CrossRefzbMATHGoogle Scholar
  11. 11.
    Fridrich, J., Filler, T.: Practical methods for minimizing embedding impact in steganography. In: Proceedings SPIE, EI, Security, Steganography, and Watermarking of Multimedia Contents IX, San Jose, CA, January 29-February 1, vol. 6505, pp. 2–3 (2007)Google Scholar
  12. 12.
    Fridrich, J., Goljan, M., Soukal, D.: Perturbed quantization steganography. ACM Multimedia System Journal 11(2), 98–107 (2005)CrossRefGoogle Scholar
  13. 13.
    Fridrich, J., Pevný, T., Kodovský, J.: Statistically undetectable JPEG steganography: Dead ends, challenges, and opportunities. In: Proceedings of the 9th ACM Multimedia & Security Workshop, Dallas, TX, September 20-21, pp. 3–14 (2007)Google Scholar
  14. 14.
    Goljan, M., Fridrich, J., Holotyak, T.: New blind steganalysis and its implications. In: Proceedings SPIE, EI, Security, Steganography, and Watermarking of Multimedia Contents VIII, San Jose, CA, vol. 6072, pp. 1–13 (2006)Google Scholar
  15. 15.
    Guyon, I., Gunn, S., Nikravesh, M., Zadeh, L.A.: Feature Extraction, Foundations and Applications. Springer, Heidelberg (2006)CrossRefzbMATHGoogle Scholar
  16. 16.
    Harmsen, J.J., Pearlman, W.A.: Steganalysis of additive noise modelable information hiding. In: Proceedings SPIE, EI, Security and Watermarking of Multimedia Contents V, Santa Clara, CA, January 21-24, vol. 5020, pp. 131–142 (2003)Google Scholar
  17. 17.
    Ker, A.D., Böhme, R.: Revisiting weighted stego-image steganalysis. In: Proceedings SPIE, EI, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, San Jose, CA, January 27-31, vol. 6819, p. 5-1–5-17 (2008)Google Scholar
  18. 18.
    Ker, A.D., Pevný, T., Kodovský, J., Fridrich, J.: The Square Root Law of steganographic capacity. In: Proceedings of the 10th ACM Multimedia & Security Workshop, Oxford, UK, September 22-23, pp. 107–116 (2008)Google Scholar
  19. 19.
    Kim, Y., Duric, Z., Richards, D.: Modified matrix encoding technique for minimal distortion steganography. In: Camenisch, J.L., Collberg, C.S., Johnson, N.F., Sallee, P. (eds.) IH 2006. LNCS, vol. 4437, pp. 314–327. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  20. 20.
    Kodovský, J., Fridrich, J.: On completeness of feature spaces in blind steganalysis. In: Proceedings of the 10th ACM Multimedia & Security Workshop, Oxford, UK, September 22-23, pp. 123–132 (2008)Google Scholar
  21. 21.
    Kodovský, J., Pevný, T., Fridrich, J.: Modern steganalysis can detect YASS. In: Proceedings SPIE, EI, Media Forensics and Security XII, San Jose, CA (2010)Google Scholar
  22. 22.
    Pevný, T., Bas, P., Fridrich, J.: Steganalysis by subtractive pixel adjacency matrix. In: Proceedings of the 11th ACM Multimedia & Security Workshop, Princeton, NJ, September 7-8, pp. 75–84 (2009)Google Scholar
  23. 23.
    Pevný, T., Fridrich, J.: Benchmarking for steganography. In: Solanki, K., Sullivan, K., Madhow, U. (eds.) IH 2008. LNCS, vol. 5284, pp. 251–267. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  24. 24.
    Ryabko, B., Ryabko, D.: Asymptotically optimal perfect steganographic systems. Problems of Information Transmission 45(2), 184–190 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  25. 25.
    Sachnev, V., Kim, H.J., Zhang, R.: Less detectable JPEG steganography method based on heuristic optimization and BCH syndrome coding. In: Proceedings of the 11th ACM Multimedia & Security Workshop, September 7-8, pp. 131–140 (2009)Google Scholar
  26. 26.
    Sallee, P.: Model-based steganography. In: Kalker, T., Cox, I., Ro, Y.M. (eds.) IWDW 2003. LNCS, vol. 2939, pp. 154–167. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  27. 27.
    Ullerich, C., Westfeld, A.: Weaknesses of MB2. In: Shi, Y.Q., Kim, H.-J., Katzenbeisser, S. (eds.) IWDW 2007. LNCS, vol. 5041, pp. 127–142. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  28. 28.
    Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, New York (1995)CrossRefzbMATHGoogle Scholar
  29. 29.
    Wang, Y., Moulin, P.: Perfectly secure steganography: Capacity, error exponents, and code constructions. IEEE Transactions on Information Theory, Special Issue on Security 55(6), 2706–2722 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  30. 30.
    Westfeld, A.: High capacity despite better steganalysis (F5 – a steganographic algorithm). In: Moskowitz, I.S. (ed.) IH 2001. LNCS, vol. 2137, pp. 289–302. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  31. 31.
    Zhang, X., Zhang, W., Wang, S.: Efficient double-layered steganographic embedding. Electronics Letters 43, 482–483 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Tomáš Pevný
    • 1
  • Tomáš Filler
    • 2
  • Patrick Bas
    • 3
  1. 1.Czech Technical University in PragueCzech Republic
  2. 2.State University of New York in BinghamtonUSA
  3. 3.CNRS - LAGIS, LilleFrance

Personalised recommendations