26-05-2012, 05:55 PM
An Adaptive Steganographic Technique Based on Integer Wavelet Transform
[attachment=23246]
INTRODUCTION
Steganography is the art and science of hiding secret data in
plain sight without being noticed within an innocent cover
data so that it can be securely transmitted over a network. The
word steganography is originally composed of two Greek
words steganos and graphia, which means "covered writing".
The use of steganography dates back to ancient times where it
was used by romans and ancient Egyptians. The interest in
modem digital Steganography started by Simmons in 1983
[1] when he presented the problem of two prisoners wishing
to escape and being watched by the warden that blocks any
suspicious data communicated between them and passes only
normal looking one. Any digital file such as image, video,
audio, text or IP packets can be used to hide secret message.
INTEGER WAVELET TRANSFORM
Generally wavelet domain allows us to hide data in regions
that the human visual system (HVS) is less sensitive to, such
as the high resolution detail bands (HL, LH and HH), Hiding
data in these regions allow us to increase the robustness while
maintaining good visual quality. Integer wavelet transform
maps an integer data set into another integer data set. In
discrete wavelet transform, the used wavelet filters have
floating point coefficients so that when we hide data in their
coefficients any truncations of the floating point values of the
pixels that should be integers may cause the loss of the
hidden information which may lead to the failure of the data
hiding system [II]. To avoid problems of floating point
precision of the wavelet filters when the input data is integer
as in digital images, the output data will no longer be integer
which doesn't allow perfect reconstruction of the input image
[12] and in this case there will be no loss of information
through forward and inverse transform [II].
PROPOSED SYSTEM
The proposed system is an adaptive data hiding scheme, in
which randomly selected integer wavelet coefficients of the
cover image are modified with secret message bits. Each of
these selected coefficients hide different number of message
bits according to the hiding capacity function, the capacity
function used is a modified version of the one in [6]. After
data insertion we apply optimum pixel adjustment algorithm
in [4] to reduce the error induced due to data insertion. The
block diagram is shown in "Fig. 2". We can say that the
proposed system is classified into three cases of operation
according to different applications; Low hiding capacity with
good visual quality (high value of peak signal to noise ratio
"PSNR"), average hiding capacity with reasonable visual
quality and high hiding capacity with low visual quality. We
discuss each of these cases in next section.
CONCLUSIONS
In this paper we proposed a novel data hiding scheme that
hides data into the integer wavelet coefficients of an image.
The system combines an adaptive data hiding technique and
the optimum pixel adjustment algorithm to increase the
hiding capacity of the system compared to other systems. The
proposed system embeds secret data in a random order using
a secret key only known to both sender and receiver. is an
adaptive system which embeds different number of bits in
each wavelet coefficicient according to a hiding capacity
function in order to maximize the hiding capacity without
sacrificing the visual quality of resulting stego image. The
proposed system also minimizes the difference between
original coefficients values and modified values by using the
optimum pixel adjustment algorithm. The proposed scheme
was classified into three cases of hiding capacity according to
different applications required by the user. Each case has
different visual quality of the stego-image. Any data type can
be used as the secret message since our experiments was
made on a binary stream of data. There was no error in the
recovered message (perfect recovery) at any hiding rate.
From the experiments and the obtained results the proposed
system proved to achieve high hiding capacity up to 48% of
the cover image size with reasonable image quality and high
security because of using random insertion of the secret
message. On the other hand the system suffers from low
robustness against various attacks such as histogram
equalization and JPEG compression.
[attachment=23246]
INTRODUCTION
Steganography is the art and science of hiding secret data in
plain sight without being noticed within an innocent cover
data so that it can be securely transmitted over a network. The
word steganography is originally composed of two Greek
words steganos and graphia, which means "covered writing".
The use of steganography dates back to ancient times where it
was used by romans and ancient Egyptians. The interest in
modem digital Steganography started by Simmons in 1983
[1] when he presented the problem of two prisoners wishing
to escape and being watched by the warden that blocks any
suspicious data communicated between them and passes only
normal looking one. Any digital file such as image, video,
audio, text or IP packets can be used to hide secret message.
INTEGER WAVELET TRANSFORM
Generally wavelet domain allows us to hide data in regions
that the human visual system (HVS) is less sensitive to, such
as the high resolution detail bands (HL, LH and HH), Hiding
data in these regions allow us to increase the robustness while
maintaining good visual quality. Integer wavelet transform
maps an integer data set into another integer data set. In
discrete wavelet transform, the used wavelet filters have
floating point coefficients so that when we hide data in their
coefficients any truncations of the floating point values of the
pixels that should be integers may cause the loss of the
hidden information which may lead to the failure of the data
hiding system [II]. To avoid problems of floating point
precision of the wavelet filters when the input data is integer
as in digital images, the output data will no longer be integer
which doesn't allow perfect reconstruction of the input image
[12] and in this case there will be no loss of information
through forward and inverse transform [II].
PROPOSED SYSTEM
The proposed system is an adaptive data hiding scheme, in
which randomly selected integer wavelet coefficients of the
cover image are modified with secret message bits. Each of
these selected coefficients hide different number of message
bits according to the hiding capacity function, the capacity
function used is a modified version of the one in [6]. After
data insertion we apply optimum pixel adjustment algorithm
in [4] to reduce the error induced due to data insertion. The
block diagram is shown in "Fig. 2". We can say that the
proposed system is classified into three cases of operation
according to different applications; Low hiding capacity with
good visual quality (high value of peak signal to noise ratio
"PSNR"), average hiding capacity with reasonable visual
quality and high hiding capacity with low visual quality. We
discuss each of these cases in next section.
CONCLUSIONS
In this paper we proposed a novel data hiding scheme that
hides data into the integer wavelet coefficients of an image.
The system combines an adaptive data hiding technique and
the optimum pixel adjustment algorithm to increase the
hiding capacity of the system compared to other systems. The
proposed system embeds secret data in a random order using
a secret key only known to both sender and receiver. is an
adaptive system which embeds different number of bits in
each wavelet coefficicient according to a hiding capacity
function in order to maximize the hiding capacity without
sacrificing the visual quality of resulting stego image. The
proposed system also minimizes the difference between
original coefficients values and modified values by using the
optimum pixel adjustment algorithm. The proposed scheme
was classified into three cases of hiding capacity according to
different applications required by the user. Each case has
different visual quality of the stego-image. Any data type can
be used as the secret message since our experiments was
made on a binary stream of data. There was no error in the
recovered message (perfect recovery) at any hiding rate.
From the experiments and the obtained results the proposed
system proved to achieve high hiding capacity up to 48% of
the cover image size with reasonable image quality and high
security because of using random insertion of the secret
message. On the other hand the system suffers from low
robustness against various attacks such as histogram
equalization and JPEG compression.