Steganalysis using higher-order image statistics

  • Authors:
  • S. Lyu;H. Farid

  • Affiliations:
  • Dept. of Comput. Sci., Dartmouth Coll., Hanover, NH, USA;-

  • Venue:
  • IEEE Transactions on Information Forensics and Security
  • Year:
  • 2006

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Abstract

Techniques for information hiding (steganography) are becoming increasingly more sophisticated and widespread. With high-resolution digital images as carriers, detecting hidden messages is also becoming considerably more difficult. We describe a universal approach to steganalysis for detecting the presence of hidden messages embedded within digital images. We show that, within multiscale, multiorientation image decompositions (e.g., wavelets), first- and higher-order magnitude and phase statistics are relatively consistent across a broad range of images, but are disturbed by the presence of embedded hidden messages. We show the efficacy of our approach on a large collection of images, and on eight different steganographic embedding algorithms.