A New Methodology in Steganalysis: Breaking Highly Undetectable Steganograpy (HUGO)

  • Gokhan Gul
  • Fatih Kurugollu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6958)


This paper presents a new methodology for the steganalysis of digital images. In principle, the proposed method is applicable to any kind of steganography at any domain. Special interest is put on the steganalysis of Highly Undetectable Steganography (HUGO). The proposed method first extracts features via applying a function to the image, constructing the k variate probability density function (PDF) estimates, and downsampling it by a suitable downsampling algorithm. The extracted feature vectors are then further optimized in order to increase the detection performance and reduce the computational time. Finally using a supervised classification algorithm such as SVM, steganalysis is performed. The proposed method is capable of detecting BOSSRank image set with an accuracy of 85%.


Feature Vector Feature Selection Discrete Cosine Transform Detection Performance Cover 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 2011

Authors and Affiliations

  • Gokhan Gul
    • 1
  • Fatih Kurugollu
    • 2
  1. 1.Signal Processing Group, Institute of TelecommunicationsTechnische Universität DarmstadtDarmstadtGermany
  2. 2.School of Electronics, Electrical Engineering and Computer ScienceQueen’s UniversityBelfastUK

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