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Abstract: The process of information hiding is modeled in the context of additive noise. Under an independence assumption, the histogram of the stegomessage is a convolution of the noise probability mass function (PMF) and the original histogram. In the frequency domain this convolution is viewed as a multiplication of the histogram characteristic function (HCF) and the noise characteristic function. Least significant bit, spread spectrum, and DCT hiding methods for images are analyzed in this framework. ... (Update)
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BibTeX entry: (Update)
J. J. Harmsen and W. A. Pearlman, "Steganalysis of additive noise modelable information hiding," in Proc. SPIE Electronic Imaging 5022, (Santa Clara, CA), Jan. 21--24, 2003. http://citeseer.ist.psu.edu/harmsen03steganalysis.html More
@inproceedings{ harmsen03steganalysis,
author = {J J Harmsen and W A Pearlman},
title = {Steganalysis of additive noise modelable information hiding},
booktitle = {Proc. SPIE Electronic Imaging 5022},
year = 2003,
address = {Santa Clara, CA},
month = jan # " 21--24,",
url = {citeseer.ist.psu.edu/harmsen03steganalysis.html} }
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Documents on the same site (http://www.cipr.rpi.edu/~harmsj/pubs.html):
Kernel Fisher Discriminant for Steganalysis of JPEG Hiding.. - Harmsen, Pearlman (2004) (Correct)
Fast Additive Noise Steganalysis - Harmsen, Bowers, Pearlman (2004) (Correct)
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