Probabilistic Methods for a Japanese Syllable Cipher

  • Sujith Ravi
  • Kevin Knight
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5459)

Abstract

This paper attacks a Japanese syllable-substitution cipher. We use a probabilistic, noisy-channel framework, exploiting various Japanese language models to drive the decipherment. We describe several innovations, including a new objective function for searching for the highest-scoring decipherment. We include empirical studies of the relevant phenomena, and we give improved decipherment accuracy rates.

Keywords

Substitution cipher decipherment language modeling 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Merialdo, B.: Tagging English text with a probabilistic model. Computational Linguistics 20(2), 155–171 (1994)Google Scholar
  2. 2.
    Peleg, S., Rosenfeld, A.: Breaking substitution ciphers using a relaxation algorithm. Comm. ACM 22(11), 598–605 (1979)CrossRefGoogle Scholar
  3. 3.
    Olson, E.: Robust dictionary attack of short simple substitution ciphers. Cryptologia 31(4), 332–342 (2007)CrossRefGoogle Scholar
  4. 4.
    Knight, K., Yamada, K.: A computational approach to deciphering unknown scripts. In: Proceedings of the ACL Workshop on Unsupervised Learning in Natural Language Processing (1999)Google Scholar
  5. 5.
    Knight, K., Nair, A., Rathod, N., Yamada, K.: Unsupervised analysis for decipherment problems. In: Proceedings of the COLING/ACL (2006)Google Scholar
  6. 6.
    Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society Series 39(4), 1–38 (1977)Google Scholar
  7. 7.
    Ravi, S., Knight, K.: Attacking decipherment problems optimally with low-order n-gram models. In: Proceedings of the EMNLP (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sujith Ravi
    • 1
  • Kevin Knight
    • 1
  1. 1.Information Sciences Institute, Computer Science DepartmentUniversity of Southern CaliforniaMarina del ReyUSA

Personalised recommendations