Attacks on Steganographic Systems

Breaking the Steganographic Utilities EzStego, Jsteg, Steganos, and S-Tools-and Some Lessons Learned
  • Andreas Westfeld
  • Andreas Pfitzmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1768)


The majority of steganographic utilities for the camouflage of confidential communication suffers from fundamental weaknesses. On the way to more secure steganographic algorithms, the development of attacks is essential to assess security. We present both visual attacks, making use of the ability of humans to clearly discern between noise and visual patterns, and statistical attacks which are much easier to automate.

The visual attacks presented here exemplify that at least EzStego v2.0b3, Jsteg v4, Steganos v1.5, and S-Tools v4.0 suffer from the misassumption that least significant bits of image data are uncorrelated noise. Beyond that, this paper introduces more objective methods to detect steganography by statistical means.


Secret Message JPEG Compression Information Hiding Statistical Attack JPEG Image 
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 2000

Authors and Affiliations

  • Andreas Westfeld
    • 1
  • Andreas Pfitzmann
    • 1
  1. 1.Department of Computer ScienceDresden University of TechnologyDresdenGermany

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