Skip to main content

Steganography Based on Pattern Languages

  • 1396 Accesses

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 9618)

Abstract

In order to transmit secret messages such that the information exchange itself cannot be detected, steganography needs a channel, a set of strings with some distribution that occur in an ordinary communication. The elements of such a language or concept are called coverdocuments. The question how to design secure stegosystems for natural classes of languages is investigated for pattern languages. We present a randomized modification scheme for strings of a pattern language that can reliably encode arbitrary messages and is almost undetectable.

Keywords

  • Language-based cryptography
  • Steganography
  • Pattern

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Angluin, D.: Finding patterns common to a set of strings. JCSS 21(1), 46–62 (1980)

    MathSciNet  MATH  Google Scholar 

  2. Bellare, M., Desai, A., Jokipii, E., Rogaway, P.: A concrete security treatment of symmetric encryption. In: Proceedings of 38th Annual Symposium on Foundations of Computer Science, FOCS, pp. 394–403. IEEE (1997)

    Google Scholar 

  3. Case, J., Jain, S., Le, T.D., Ong, Y.S., Semukhin, P., Stephan, F.: Automatic learning of subclasses of pattern languages. Inf. Comput. 218, 17–35 (2012)

    CrossRef  MathSciNet  MATH  Google Scholar 

  4. Case, J., Jain, S., Reischuk, R., Stephan, F., Zeugmann, T.: Learning a subclass of regular patterns in polynomial time. TCS 364(1), 115–131 (2006)

    CrossRef  MathSciNet  MATH  Google Scholar 

  5. Dedić, N., Itkis, G., Reyzin, L., Russell, S.: Upper and lower bounds on black-box steganography. J. Cryptol. 22(3), 365–394 (2009)

    CrossRef  MATH  Google Scholar 

  6. Ernst, M., Liśkiewicz, M., Reischuk, R.: Algorithmic learning for steganography: proper learning of k-term DNF formulas from positive samples. In: Elbassioni, K., Makino, K. (eds.) ISAAC 2015. LNCS, vol. 9472, pp. 151–162. Springer, Heidelberg (2015)

    CrossRef  Google Scholar 

  7. Hopper, N., von Ahn, L., Langford, J.: Provably secure steganography. IEEE Trans. Comput. 58(5), 662–676 (2009)

    CrossRef  MathSciNet  Google Scholar 

  8. Jerrum, M., Valiant, L.G., Vazirani, V.V.: Random generation of combinatorial structures from a uniform distribution. TCS 43, 169–188 (1986)

    CrossRef  MathSciNet  MATH  Google Scholar 

  9. Katzenbeisser, S., Petitcolas, F.A.: Defining security in steganographic systems. In: Electronic Imaging 2002, SPIE, pp. 50–56 (2002)

    Google Scholar 

  10. Ker, A.D., Bas, P., Böhme, R., Cogranne, R., Craver, S., Filler, T., Fridrich, J., Pevnỳ, T.: Moving steganography and steganalysis from the laboratory into the real world. In: Proceedings 1st ACM WS on Information Hiding and Multimedia Security, pp. 45–58. ACM (2013)

    Google Scholar 

  11. Ker, A.D., Pevný, T., Kodovský, J., Fridrich, J.J.: The square root law of steganographic capacity. In: Proceedings of 10th WS Multimedia & Security, pp. 107–116 (2008)

    Google Scholar 

  12. Lange, S., Wiehagen, R.: Polynomial-time inference of arbitrary pattern languages. New Gener. Comput. 8(4), 361–370 (1991)

    CrossRef  MATH  Google Scholar 

  13. Liśkiewicz, M., Reischuk, R., Wölfel, U.: Grey-box steganography. TCS 505, 27–41 (2013)

    CrossRef  MATH  Google Scholar 

  14. Reidenbach, D.: A negative result on inductive inference of extended pattern languages. In: Cesa-Bianchi, N., Numao, M., Reischuk, R. (eds.) ALT 2002. LNCS (LNAI), vol. 2533, pp. 308–320. Springer, Heidelberg (2002)

    CrossRef  Google Scholar 

  15. Reischuk, R., Zeugmann, T.: An average-case optimal one-variable pattern language learner. JCSS 60(2), 302–335 (2000)

    MathSciNet  MATH  Google Scholar 

  16. Salomaa, A.: Patterns. EATCS Bull. 54, 46–62 (1994)

    Google Scholar 

  17. Shinohara, T.: Polynomial time inference of extended regular pattern languages. In: Goto, E., Furukawa, K., Nakajima, R., Nakata, I., Yonezawa, A. (eds.) RIMS Symposia on Software Science and Engineering. LNCS, pp. 115–127. Springer, Heidelberg (1983)

    CrossRef  Google Scholar 

  18. Shinohara, T., Arikawa, S.: Pattern inference. In: Lange, S., Jantke, K.P. (eds.) GOSLER 1994. LNCS, vol. 961, pp. 259–291. Springer, Heidelberg (1995)

    CrossRef  Google Scholar 

  19. Stephan, F., Yoshinaka, R., Zeugmann, T.: On the parameterised complexity of learning patterns. In: Proceedings of 26th Computer and Information Sciences, pp. 277–281 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sebastian Berndt .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Berndt, S., Reischuk, R. (2016). Steganography Based on Pattern Languages. In: Dediu, AH., Janoušek, J., Martín-Vide, C., Truthe, B. (eds) Language and Automata Theory and Applications. LATA 2016. Lecture Notes in Computer Science(), vol 9618. Springer, Cham. https://doi.org/10.1007/978-3-319-30000-9_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-30000-9_30

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29999-0

  • Online ISBN: 978-3-319-30000-9

  • eBook Packages: Computer ScienceComputer Science (R0)