• DocumentCode
    3398218
  • Title

    Do you see what i see?

  • Author

    Cerkez, P.S.

  • Author_Institution
    DCS Corp., Lexington, MD, USA
  • fYear
    2013
  • fDate
    23-25 Oct. 2013
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Semagrams are a subset of steganography. When a message is transmitted in a non-textual format, (i.e., in the visual content of an image), it is referred to as a semagram. While semagrams are relatively easy to create (as shown in published papers covering hiding techniques), detecting a hidden message in or embedded as an image-based semagram is a greater magnitude of difficultly than typical digital steganography. US Patents issued based on semagram technology show that this feature has been exploited in the copyright/watermarking world to increase protection. In a semagram, the image is the message and they work well for simple messages and dead drops. Attacks on semagrams are primarily visual examinations of artifacts. In the counter-espionage world, the rule of the thumb is that there is always a message hidden in an image or graphic, it is simply up to the steganalyst to find it. In short, detecting semagrams is a matter of recognizing patterns of patterns that represent a hidden message within an image. This presentation provides a brief summary of the technology underlying semagrams, present a short non-technical discussion of the technology used in the attack on semagrams, followed by a discussion on current work and planned future implementations of the proven semagram detection ANN. It will focus on extending the ANN to other domains (e.g., non-visual spectrums, multi/cross spectrum correlation, scene identification, image classification) and efforts to improve the processing speed and throughput via parallel/distributed methods.
  • Keywords
    copyright; image recognition; image watermarking; neural nets; steganography; US patents; copyright-watermarking world; counter-espionage world; digital steganography; hidden message; image-based semagram; nontextual format; parallel-distributed methods; pattern detection; semagram detection ANN; semagram recognition; steganography; visual examinations; Artificial neural networks; Context; Image coding; Pattern recognition; Testing; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Imagery Pattern Recognition Workshop (AIPR): Sensing for Control and Augmentation, 2013 IEEE
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/AIPR.2013.6749313
  • Filename
    6749313