Towards digital video steganalysis using asymptotic memoryless detection

  • Authors:
  • Julien S. Jainsky;Deepa Kundur;Don R. Halverson

  • Affiliations:
  • Texas A&M University, College Station, TX;Texas A&M University, College Station, TX;Texas A&M University, College Station, TX

  • Venue:
  • Proceedings of the 9th workshop on Multimedia & security
  • Year:
  • 2007

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Abstract

This paper studies the potential for passive steganalysis in correlated image frames using non-classical detection theory. In particular, an algorithm for digital video steganalysis, named MoViSteg for Motion-based Video Steganalysis, is developed that exploits the temporal correlation among individual image frames in video signals to enhance steganalysis performance. The method differs from prior art in the use of motion interpolation and non-classical asymptotic memoryless detection that we believe is well-suited for video steganalysis. Results and discussion are provide in order to demonstrate the potential of our ideas for intrusion detection in a broad class of emerging multimedia applications.