Weaknesses of MB2

  • Christian Ullerich
  • Andreas Westfeld
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5041)


Model-based steganography is a promising approach for hidden communication in JPEG images with high steganographic capacity and competitive security. In this paper we propose an attack, which is based on coefficient types that can be derived from the blockiness adjustment of MB2. We derive 30 new features to be used in combination with existing blind feature sets leading to a remarkable reduction of the false positive rate (about 10:1) for very low embedding rates (0.02 bpc). We adapt Sallee’s model-based approach for steganalysis where the Cauchy model itself is used to detect Cauchy model-based embedded messages. We apply a gradient aware blockiness measure for improved reliability in the detection of MB1. We evaluate our proposed methods based on a set of about 3000 images.


Cover Image Detection Reliability JPEG Image Quadratic Discriminant Analysis Block Artefact 
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 2008

Authors and Affiliations

  • Christian Ullerich
    • 1
  • Andreas Westfeld
    • 1
  1. 1.Institute for System ArchitectureTechnische Universität DresdenDresdenGermany

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