A Practical and Effective Approach to Large-Scale Automated Linguistic Steganography

  • Mark Chapman
  • George I. Davida
  • Marc Rennhard
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2200)


Several automated techniques exist to transform ciphertext into text that “looks like” natural-language text while retaining the ability to recover the original ciphertext. This transformation changes the ciphertext so that it doesn’t attract undue attention from, for example, attackers or agencies or organizations that might want to detect or censor encrypted communication. Although it is relatively easy to generate a small sample of quality text, it is challenging to be able to generate large texts that are “meaningful” to a human reader and which appear innocuous.

This paper expands on a previous approach that used sentence models and large dictionaries of words classified by part-of-speech [7]. By using an “extensible contextual template” approach combined with a synonymbased replacement strategy, much more realistic text is generated than was possible with NICETEXT.


Secret Message Sentence Structure Human Reader Realistic Text Large Dictionary 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Mark Chapman
    • 1
  • George I. Davida
    • 2
  • Marc Rennhard
    • 3
  1. 1.Omni Tech CorporationPewaukeeUSA
  2. 2.Department of EE & CSUniversity of Wisconsin-MilwaukeeMilwaukeeUSA
  3. 3.Computer Engineering and Networks Laboratory (TIK)Swiss Federal Institute of TechnologyZurich

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