the $+1$ or $-1$ is randomly added to the cover pixel LSB value
only if this one does not correspond to the secret bit.
%TODO : modifier ceci
-Since it is possible to make that probabilities of increasing or decreasing the pixel value, for instance by considering well-encrypted hidden messages, usual statistical approaches
+By considering well-encrypted hidden messages, probabilities of increasing or ofdecreasing value of pixels are equal. Then usual statistical approaches
cannot be applied here to discover stego-contents in LSBM.
The most accurate detectors for this matching are universal steganalysers such as~\cite{LHS08,DBLP:conf/ih/Ker05,FK12},
which classify images according to extracted features from neighboring elements of residual noise.
- Finally, LSB matching revisited (LSBMR) has been recently introduced in~\cite{Mielikainen06}.
+ Finally, LSB matching revisited (LSBMR) has recently been introduced in~\cite{Mielikainen06}.
It works as follows: for a given pair of pixels, the LSB
of the first pixel carries a first bit of the secret message, while the parity relationship
(odd/even combination) of the two pixel values carries
Instead of (efficiently) modifying LSBs, there is also a need to select pixels whose value
modification minimizes a distortion function.
- This distortion may be computed thanks to feature vectors that are embedded for instance in steganalysers
+ This distortion may be computed thanks to feature vectors that are embedded for instance in the steganalysers
referenced above.
Highly Undetectable steGO (HUGO) method~\cite{DBLP:conf/ih/PevnyFB10} is one of the most efficient instance of such a scheme.
It takes into account so-called SPAM features
to avoid overfitting a particular
steganalyser. Thus a distortion measure for each pixel is individually determined as the sum of the differences between
the features of the SPAM computed from the cover and from the stego images.
- Thanks to this features set, HUGO allows to embed $7\times$ longer messages with the same level of
- indetectability than LSB matching.
+ Thanks to this features set, HUGO allows to embed messages that are $7\times$ longer than the former ones with the same level of
+ indetectability as LSB matching.
However, this improvement is time consuming, mainly due to the distortion function
computation.
approaches being detailed in~\cite{Luo:2010:EAI:1824719.1824720} and
in~\cite{DBLP:journals/eswa/ChenCL10}.
In the former, the authors present the Edge Adaptive
- Image Steganography based on LSB matching revisited further denoted as to
+ Image Steganography based on LSB matching revisited further denoted as
EAISLSBMR. This approach selects sharper edge
regions with respect
to a given embedding rate: the larger the number of bits to be embedded, the coarser
the edge regions are.
- Then the data hiding algorithm is achieved by applying LSBMR on pixels of these regions.
+ Then the data hiding algorithm is achieved by applying LSBMR on some of the pixels of these regions.
The authors show that their proposed method is more efficient than all the LSB, LSBM, and LSBMR approaches
thanks to extensive experiments.
However, it has been shown that the distinguishing error with LSB embedding is lower than
the one with some binary embedding~\cite{DBLP:journals/tifs/FillerJF11}.
- We thus propose to take benefit of these optimized embeddings, provided they are not too time consuming.
+ We thus propose to take advantage of these optimized embeddings, provided they are not too time consuming.
In the latter, an hybrid edge detector is presented followed by an ad hoc
embedding.
The Edge detection is computed by combining fuzzy logic~\cite{Tyan1993}
% but to exclude the LSBs which are modified.
Finally, even if the steganalysis discipline
- has done great leaps forward these last years, it is currently impossible to prove rigorously
+ has known great innovations these last years, it is currently impossible to prove rigorously
that a given hidden message cannot be recovered by an attacker.
This is why we add to our scheme a reasonable
message encryption stage, to be certain that,
-\documentclass[10pt]{article}
+\documentclass{comjnl}
+\usepackage{epsfig,psfrag}
+\usepackage{graphicx}
+\usepackage{color}
+\usepackage{dsfont}
\usepackage{url}
\usepackage{graphicx}
\usepackage{mathptmx,amsmath,amssymb,bm}
\usepackage{mathtools,etoolbox}
\usepackage{cite}
\usepackage{setspace}
-\usepackage[switch, modulo]{lineno}
+\usepackage{lineno}
+
+
+\begin{document}
+%\doublespacing
+%\linenumbers
- \title[STABYLO]{STABYLO:
- a lightweight edge-based steganographic approach}
- \author{Jean-Fran\c cois Couchot, Raphael Couturier, and Christophe Guyeux\thanks{Authors in alphabetic order}}
+ \DeclarePairedDelimiter{\abs}{\lvert}{\rvert}
+
+ % correct bad hyphenation here
+ \hyphenation{op-tical net-works semi-conduc-tor}
+
+
+
+
++\title[STABYLO]{STABYLO:
++a lightweight edge-based steganographic approach}
+
++\author{Jean-Fran\c cois Couchot, Raphael Couturier, and Christophe Guyeux\thanks{Authors in alphabetic order}}
+
+\affiliation{ FEMTO-ST Institute, UMR 6174 CNRS\\
+ Computer Science Laboratory DISC,
+ University of Franche-Comt\'{e},
+ Besan\c con, France.}
+\email{\{raphael.couturier, jean-francois.couchot, christophe.guyeux\}@univ-fcomte.fr}
-
-
-\title{STABYLO:
-a lightweight %stego-secure
-edge-based steganographic approach}
-
-
+\shortauthors{J.-F. Couchot, R. Couturier, and C. Guyeux}
-\linenumbers
+\received{...}
+\revised{...}
-\author{Jean-Fran\c cois Couchot, Raphael Couturier, and Christophe Guyeux*\\
- $*:$ Authors in alphabetic order.\\
- FEMTO-ST Institute, UMR 6174 CNRS\\
- Computer Science Laboratory DISC,
- University of Franche-Comt\'{e},
- Besan\c con, France.
-}
-%\authorrunning{J.-F. Couchot, R. Couturier, and C. Guyeux}
-%\mail{jean-francois.couchot@femto-st.fr}
-
\newcommand{\JFC}[1]{\begin{color}{green}\textit{#1}\end{color}}
\newcommand{\RC}[1]{\begin{color}{red}\textit{}\end{color}}
\newcommand{\CG}[1]{\begin{color}{blue}\textit{}\end{color}}
%IEEEtran, journal, \LaTeX, paper, template.
- \keywords{Steganography, least-significant-bit (LSB)-based steganography, edge detection, Canny filter, security, syndrome trellis codes}
+ %\keywords{Steganography, least-significant-bit (LSB)-based steganography, edge detection, Canny filter, security, syndrome trellis codes}
+
+
+
+
+
-\begin{document}
-\maketitle
-\doublespacing
+
- \begin{abstract}
+
+ \begin{abstract}
++
A novel steganographic method called STABYLO is introduced in
this research work.
Its main advantage is to be much lighter than the so-called
Highly Undetectable steGO (HUGO) scheme, a well-known state of the art
- steganographic process in spatial domain.
+ steganographic process in the spatial domain.
Additionally to this effectiveness,
quite comparable results through noise measures like PSNR-HVS-M,
and weighted PSNR (wPSNR) are obtained.
a scheme that can reasonably face up-to-date steganalysers.
\end{abstract}
-
-
--
+\maketitle
-
\section{Introduction}\label{sec:intro}
\input{intro.tex}
for minimizing distortion.
After having introduced with details the proposed method,
we have evaluated it through noise measures (namely, the PSNR, PSNR-HVS-M,
- BIQI, and weighted PSNR) and using well-established steganalysers.
+ BIQI, and weighted PSNR) and we have used well-established steganalysers.
% Of course, other detectors like the fuzzy edge methods
% deserve much further attention, which is why we intend
% to investigate systematically all of these detectors in our next work.
-
+c
For future work, the authors' intention is to investigate systematically
all the existing edge detection methods, to see if the STABYLO evaluation scores can
systematic replacement of all the LSBs of edges by binary digits provided
by the BBS generator will be investigated, and the consequences of such a
replacement, in terms of security, will be discussed.
- Furthermore, we plan to investigate information hiding on other models, high frequency for JPEG encoding for instance.
+ Furthermore, we plan to investigate information hiding on other models, such as high frequency for JPEG encoding.
-\bibliographystyle{plain}
+\bibliographystyle{compj}
\bibliography{biblio}
the cover pixel selection (Sect.~\ref{sub:edge}),
the adaptive payload considerations (Sect.~\ref{sub:adaptive}),
and how the distortion has been minimized (Sect.~\ref{sub:stc}).
- The message extraction is finally presented (Sect.~\ref{sub:extract}) and a running example ends this section (Sect.~\ref{sub:xpl}).
+ The message extraction is then presented (Sect.~\ref{sub:extract}) and a running example ends this section (Sect.~\ref{sub:xpl}).
The flowcharts given in Fig.~\ref{fig:sch}
summarize our steganography scheme denoted by
STABYLO, which stands for STeganography with cAnny, Bbs, binarY embedding at LOw cost.
- What follows are successively details of the inner steps and flows inside
- both the embedding stage (Fig.~\ref{fig:sch:emb})
- and the extraction one (Fig.~\ref{fig:sch:ext}).
+ What follows are successively some details of the inner steps and the flows both inside
+ the embedding stage (Fig.~\ref{fig:sch:emb})
+ and inside the extraction one (Fig.~\ref{fig:sch:ext}).
Let us first focus on the data embedding.
- \begin{figure*}[t]
+ \begin{figure*}%[t]
\begin{center}
\subfloat[Data Embedding.]{
\begin{minipage}{0.49\textwidth}
\end{center}
\end{minipage}
\label{fig:sch:emb}
- }%\hfill
+ }
+
\subfloat[Data Extraction.]{
\begin{minipage}{0.49\textwidth}
\begin{center}
\subsection{Security considerations}\label{sub:bbs}
- Among methods of message encryption/decryption
+ Among methods of the message encryption/decryption
(see~\cite{DBLP:journals/ejisec/FontaineG07} for a survey)
we implement the Blum-Goldwasser cryptosystem~\cite{Blum:1985:EPP:19478.19501}
that is based on the Blum Blum Shub~\cite{DBLP:conf/crypto/ShubBB82}
As far as fuzzy edge methods are concerned, they are obviously based on fuzzy logic to highlight edges.
Canny filters, on their parts, are an old family of algorithms still remaining a state of the art edge detector. They can be well-approximated by first-order derivatives of Gaussians.
- As the Canny algorithm is well known and studied, fast, and implementable
+ As the Canny algorithm is fast, well known, has been studied in depth, and is implementable
on many kinds of architectures like FPGAs, smartphones, desktop machines, and
GPUs, we have chosen this edge detector for illustrative purpose.
Two methods may further be applied to select bits that
will be modified.
The first one randomly chooses the subset of pixels to modify by
- applying the BBS PRNG again. This method is further denoted as to \emph{sample}.
+ applying the BBS PRNG again. This method is further denoted as a \emph{sample}.
Once this set is selected, a classical LSB replacement is applied to embed the
stego content.
The second method is a direct application of the
In this example, the cover image is Lena,
which is a $512\times512$ image with 256 grayscale levels.
The message is the poem Ulalume (E. A. Poe), which is constituted by 104 lines, 667
- words, and 3754 characters, \textit{i.e.}, 30032 bits.
+ words, and 3,754 characters, \textit{i.e.}, 30,032 bits.
Lena and the first verses are given in Fig.~\ref{fig:lena}.
\begin{figure}
\begin{center}
- \begin{minipage}{0.4\linewidth}
- \includegraphics[width=3cm]{Lena.eps}
+ \begin{minipage}{0.49\linewidth}
+ \begin{center}
+ \includegraphics[scale=0.20]{Lena.eps}
+ \end{center}
\end{minipage}
- \begin{minipage}{0.59\linewidth}
+ \begin{minipage}{0.49\linewidth}
\begin{flushleft}
\begin{scriptsize}
The skies they were ashen and sober;\linebreak
\caption{Cover and message examples} \label{fig:lena}
\end{figure}
- The edge detection returns 18641 and 18455 pixels when $b$ is
+ The edge detection returns 18,641 and 18,455 pixels when $b$ is
respectively 7 and 6. These edges are represented in Figure~\ref{fig:edge}.
\begin{minipage}{0.49\linewidth}
\begin{center}
%\includegraphics[width=5cm]{emb.pdf}
- \includegraphics[scale=0.15]{edge7.eps}
+ \includegraphics[scale=0.20]{edge7.eps}
\end{center}
\end{minipage}
%\label{fig:sch:emb}
\begin{minipage}{0.49\linewidth}
\begin{center}
%\includegraphics[width=5cm]{rec.pdf}
- \includegraphics[scale=0.15]{edge6.eps}
+ \includegraphics[scale=0.20]{edge6.eps}
\end{center}
\end{minipage}
%\label{fig:sch:ext}
- Only 9320 bits (resp. 9227 bits) are available for embedding
+ Only 9,320 bits (resp. 9,227 bits) are available for embedding
in the former configuration where $b$ is 7 (resp. where $b$ is 6).
In both cases, about the third part of the poem is hidden into the cover.
Results with \emph{adaptive+STC} strategy are presented in
\begin{minipage}{0.49\linewidth}
\begin{center}
%\includegraphics[width=5cm]{emb.pdf}
- \includegraphics[scale=0.15]{lena7.eps}
+ \includegraphics[scale=0.20]{lena7.eps}
\end{center}
\end{minipage}
%\label{fig:sch:emb}
\begin{minipage}{0.49\linewidth}
\begin{center}
%\includegraphics[width=5cm]{rec.pdf}
- \includegraphics[scale=0.15]{lena6.eps}
+ \includegraphics[scale=0.20]{lena6.eps}
\end{center}
\end{minipage}
%\label{fig:sch:ext}
V_{ij}= \left\{
\begin{array}{rcl}
0 & \textrm{if} & X_{ij} = Y_{ij} \\
-75 & \textrm{if} & \abs{ X_{ij} - Y_{ij}} = 1 \\
-150 & \textrm{if} & \abs{ X_{ij} - Y_{ij}} = 2 \\
-225 & \textrm{if} & \abs{ X_{ij} - Y_{ij}} = 3
+75 & \textrm{if} & \vert X_{ij} - Y_{ij} \vert = 1 \\
+150 & \textrm{if} & \vert X_{ij} - Y_{ij} \vert = 2 \\
+225 & \textrm{if} & \vert X_{ij} - Y_{ij} \vert = 3
\end{array}
\right..
$$
\begin{minipage}{0.49\linewidth}
\begin{center}
%\includegraphics[width=5cm]{emb.pdf}
- \includegraphics[scale=0.15]{diff7.eps}
+ \includegraphics[scale=0.20]{diff7.eps}
\end{center}
\end{minipage}
%\label{fig:sch:emb}
\begin{minipage}{0.49\linewidth}
\begin{center}
%\includegraphics[width=5cm]{rec.pdf}
- \includegraphics[scale=0.15]{diff6.eps}
+ \includegraphics[scale=0.20]{diff6.eps}
\end{center}
\end{minipage}
%\label{fig:sch:ext}
