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Proceedings Paper

Nonparametric steganalysis of QIM data hiding using approximate entropy
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Paper Abstract

This paper proposes a nonparametric steganalysis method for quantization index modulation (QIM) based steganography. The proposed steganalysis method uses irregularity (or randomness) in the test-image to distinguish between the cover- and the stego-image. We have shown that plain-quantization (quantization without message embedding) induces regularity in the resulting quantized-image; whereas message embedding using QIM increases irregularity in the resulting QIM-stego image. Approximate entropy, an algorithmic entropy measure, is used to quantify irregularity in the test-image. Simulation results presented in this paper show that the proposed steganalysis technique can distinguish between the cover- and the stego-image with low false rates (i.e. Pfp < 0.1 & Pfn < 0.07 for dither modulation stego and Pfp < 0.12 & Pfn < 0.002 for QIM-stego).

Paper Details

Date Published: 18 March 2008
PDF: 12 pages
Proc. SPIE 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, 681914 (18 March 2008); doi: 10.1117/12.767313
Show Author Affiliations
Hafiz Malik, Univ. of Michigan-Dearborn (United States)
Stevens Institute of Technology (United States)
K. P. Subbalakshmi, Stevens Institute of Technology (United States)
R. Chandramouli, Stevens Institute of Technology (United States)


Published in SPIE Proceedings Vol. 6819:
Security, Forensics, Steganography, and Watermarking of Multimedia Contents X
Edward J. Delp; Ping Wah Wong; Jana Dittmann; Nasir D. Memon, Editor(s)

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