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Steganalysis using higher-order image statistics

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2 Author(s)
S. Lyu ; Dept. of Comput. Sci., Dartmouth Coll., Hanover, NH, USA ; H. Farid

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.

Published in:

IEEE Transactions on Information Forensics and Security  (Volume:1 ,  Issue: 1 )