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How to (Possibly) Foil Multimedia Security?
Author(s)
Date Issued
2014-07-11
Date Available
2014-07-24T11:58:56Z
Abstract
Multimedia security can be foiled thanks to
Slepian’s permutation modulation. Originally proposed in 1965
for standard problems of channel and source coding in communications,
permutation codes can also provide optimum solutions
in two relevant fields: steganography (foiling hidden information
detection tests) and counterforensics (foiling forensic detection
tests). In the first scenario, permutation codes have been shown
to implement optimum perfect universal steganography (that is
to say, steganography with maximum information embedding
rate, undetectable and only relying on the empirical distribution
of the host) for histogram-based hidden information detectors.
In the second scenario, permutation codes have been shown to
implement minimum-distortion perfect counterforensics (that is
to say, forgeries which are undetectable and as close as possible to
a target forgery) for histogram-based forensic detectors. Interestingly,
both of these developments have revealed connections with
compression through theoretical bounds from the mathematical
theory of information. In steganography, the long-acknowledged
duality between perfect steganography and lossless compression
has been made explicit by permutation coding. On the other
hand, a connection between counterforensics, lossy compression
and histogram specification is also shown.
Slepian’s permutation modulation. Originally proposed in 1965
for standard problems of channel and source coding in communications,
permutation codes can also provide optimum solutions
in two relevant fields: steganography (foiling hidden information
detection tests) and counterforensics (foiling forensic detection
tests). In the first scenario, permutation codes have been shown
to implement optimum perfect universal steganography (that is
to say, steganography with maximum information embedding
rate, undetectable and only relying on the empirical distribution
of the host) for histogram-based hidden information detectors.
In the second scenario, permutation codes have been shown to
implement minimum-distortion perfect counterforensics (that is
to say, forgeries which are undetectable and as close as possible to
a target forgery) for histogram-based forensic detectors. Interestingly,
both of these developments have revealed connections with
compression through theoretical bounds from the mathematical
theory of information. In steganography, the long-acknowledged
duality between perfect steganography and lossless compression
has been made explicit by permutation coding. On the other
hand, a connection between counterforensics, lossy compression
and histogram specification is also shown.
Sponsorship
Science Foundation Ireland
Other Sponsorship
University of Saint-Étienne
Type of Material
Conference Publication
Publisher
IEEE
Start Page
1
End Page
3
Copyright (Published Version)
2014 IEEE
Language
English
Status of Item
Not peer reviewed
Conference Details
2014 13th Workshop on Information Optics (WIO), Neuchâtel, Switzerland, 7-11 July, 2014
This item is made available under a Creative Commons License
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wio14.pdf
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Format
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