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Towards Design and Implementation of
Image Authentication / Secret Message
Transmission Technique using
Steganographic Approaches
Thesis submitted for the Degree of Doctor of Philosophy (Engineering) in the
Faculty of Engineering, Technology and Management
University of Kalyani
By
Nabin Ghoshal
Under the Supervision of
Prof. Jyotsna Kumar Mandal
Department of Computer Science and Engineering
University of Kalyani
Kalyani, Nadia, West Bengal, India
January 2011
Steganography or “hidden writing” is a technique that allows one to hide binary data within an
image with the addition of very few noticeable changes. Its goal is to achieve secrete
communication through multimedia carrier e.g. image, video and audio files between two parties
those are interested in hiding. To overcome the point of attack here is always concealing the very
existence of the embedded data into the carrier. The hiding is designed to achieve efficient trade-
offs among the three conflicting goals of maximizing rate of information embedding, minimizing
distortion between the host and composite signal, and maximizing the robustness of embedding.
For decades people strove to develop innovative methods using steganographic approaches for
secrete communication. Steganography have a long and exciting history that goes back to
antique. It can be traced back to 440 BC in ancient Greece [80]. They were used a technique for
writing a secrete message on a wooden panel cover it by a wax, and then write a message on the
wax. In another situation where steganography was used by spies, prisoners, and solders during
World War II because mail was seriously inspected. So many instances were happened, in case
of postal censors crossed out anything that looked like sensitive information and prosecuted
individuals for suspicious mail. To prevent the secrete message from being delivered, censors
even randomly deleted innocent-looking sentences or entire paragraph.
Recently the interest is increasing in the digital steganography on carrier multimedia image.
Image trafficking for commercial applications across the network is increasing day by day due to
the proliferation of internet. For the exponential growth of potential computer user, secrete
communication and image authentication using steganographic approaches are the demanded
area of research. Image authentication techniques have recently gained great attention due to its
importance for a large number of multimedia applications. Digital images are increasingly
transmitted over non-secure channels such as the Internet. Therefore, military, medical and
quality control images must be protected against attempts to manipulate them; such
manipulations could tamper the decisions based on these images. To protect the authenticity of
multimedia images, several approaches have been proposed. These approaches include
conventional cryptography, fragile and semi-fragile watermarking and digital signatures that are
based on the image content. Data hiding in the image has become an important technique for
image authentication and identification. Ownership verification and authentication is the major
task for military people, research institute, and scientist. Image authentication is a technique for
inserting information into an image for identification and authentication. Fig. 1.1 and Fig. 1.2 are
shows the typical steganographic scheme and the different embodiment of data hiding
respectively.
Key Key
Cover image Stego. image Source image
Message/
Image Message/Image
Sender Receiver
Fig. 1.1: A typical image authentication process
Fig. 1.2: A different embodiment of data hiding
1.1 Cryptography, Watermarking and Provable Security
The primary tool available for data protection is encryption. Steganography and cryptography are
counter parts in digital security the obvious advantage of steganography over cryptography is
that messages do not attract attention to themselves, to messengers and to recipients also. In
cryptosystem the security can be provided by scrambling the original content i.e. ciphertext as a
result it generates the attention to eavesdroppers. Digital watermarking is the process of hiding
the watermark imperceptibly in the content. This technique was initially used in paper and
Hiding
Algorithm
Extraction
Algorithm
Fragile
Fingerprint
Data Security system
Cryptography Information Hiding
Steganography Watermarking
Linguistic Technical Robust
Imperceptible Visible
Text Audio Video
Digital
Image
Song
In Spatial
Domain
In Frequency
Domain
currency as a measure of authenticity. Data hiding primarily refers to a digital watermark which
is a piece of information hidden in a multimedia content, in such a way that it is imperceptible to
a human observer, but easily detected by a computer. The principal advantage is that the
watermark is inseparable from the content. So, information security and image authentication has
become very important to protect digital image document from unauthorized access.
The main contributions of this thesis are divided into two categories one is image authentication
under spatial domain and another is under frequency domain. The results which establish these
works fall under several categories: one bit steganography in spatial domain, two bits
steganography in spatial domain, three bits steganography in spatial domain, one bit
steganography in frequency domain, two bits steganography in frequency domain and three bits
steganography in frequency domain. Here I summarise the results in each categories.
1-bit-steganography in spatial domain (1bss)
A 1-bit-steganography for grayscale images allows two parties with a shared secrete to send
hidden messages undetectably over a public channel. The presented work emphasizes on image
protection or authentication by hiding message/image using a hash function [ ] with a session key.
The scheme uses efficient insertion within a byte, which may be conform proper unauthorised
access while passing across the networks. Another one bit steganography technique is developed
for image authentication for colour images. This work emphasizes on information and image
protection against potential enemy while being transmitted across the networks. The
authentication or ownership verification is done by hiding secret data within the source image
byte by selecting 3 x 3 masks[ ]. In each image byte within the mask one bit of secrete data is
embedded at the randomly selected position among 1st to 5
th form LSB which conform proper
authentication and identification of the image.
2-bits-steganography in spatial domain (2bss)
2-bits-authentication technique AI/HLVD[ ] for grayscale images for shearing more secrete data
between two parties. Two bits of the authenticating message/image are inserted per byte of the
source image. Here during the embedding process the embedding is done on the size of
authenticating message/image, content of the authenticating message/image and the 128 bits
message digest (MD-5) generated from the authenticating message/image. A bit wise XOR
operation has also been performed with the inserted bits and hence a 128 bits message digest
generated from source image to enhance the security. Another method is presented an image
authentication [ ] and secures message transmission technique by embedding message/image into
colour images. Authentication is done by embedding message/ image by choosing image blocks
of size 3 x 3 called mask from the source image in row major order. The dimension of
authenticating image followed by MD-5 key and then the content of authenticating
message/image are also embedded. This is followed by an XOR operation of the embedded image
with another self generated MD-5 key obtained from the source image.
3-bits-steganography in spatial domain (3bss)
The 3-bits-steganography technique FBIA [] emphasizes on information and image protection
against unauthorized access and to insert large amount of messages/image data along with
message digest MD in to the source grayscale image for image identification and also to transmit
secure message within the image. Image authentication is done by embedding message / image in
spatial domain by choosing image blocks of size 3 × 3 from the source image in row major order.
Three bits of authenticating message /image/message-digest are fabricated within each source
image byte of each image block where the position is chosen randomly using a hash function. The
second method presented [] an image/legal-document authentication and secures message
transmission technique by embedding message/image/message-digest into colour images. Image
authentication is done by embedding message/image within the image pixels of source image.
Legal document authentication is done by embedding the authenticating image and self generated
message digest (generated from signed document part) into the image part of the legal document.
Techniques proposed are implemented on the digital multimedia images in spatial domain.
Results, discussion and comparison are drawn with respect to the popular existing authentication
technique S-Tools. Comparison of these techniques with S-Tools with respect to Histogram,
Noise analysis, Standard Deviation analysis, Pick Signal-to-Noise Ratio (PSNR), Image Fidelity
(IF) and Mean Square Error (MSE) are also done. The equations are given below those are used
to calculate different parameters for comparison. Histogram analysis is mainly the visual
interpretation of original and stego. images using different techniques. Noise is calculated using
the equation 1.1, where piE and pi
S are pixel values of the i
th pixel in both the embedded and
source image respectively. Noise is computed by finding the average of 4 direct neighbour pixels
in the 3 x 3 mask (Fig. 1.3) around the pixel pi. pjE and pj
S are 4 direct neighbour of pixel pi.
Standard deviation is calculated using the equation 1.2. In equation 1.2, x is the arithmetic mean
and N is the total number of different values and xi(s) are different level of quantum values.
∑∑∑×
=
==
×
+
−
+
=nm
i
j
S
j
S
i
j
E
j
E
i pppp
Noise1
4
1
4
1
3355
--------------------------------- (1.1)
Fig. 1.3: Noise detecting mask 4 neighbour pixels
( )∑=
−=N
i
i xxN 1
2
1σ ---------------------------------------- (1.2)
��� � �
��∑ �, � ��, �
��, ---------------------------------------- (1.3)
���� � 10 ��������/���� ------------------------------------ (1.4)
� � 1 � ∑ �, � ��, ��
/ ∑ �, �
�, �, ------------------------ (1.5)
Equation 1.3 is for calculating the Mean Square Error for measuring the amount of noise
integration in the stego. image after authentication. In equation 1.3, MN is the dimension of
original image Im,n and ��, is the stego. image whose coordinates are (m,n). PSNR is calculated
by equation 1.4 where R is max (�, � ) of original image �, . For higher PSNR value in dB
indicates minimum noise integration. IF is calculated using the equation 1.5. The calculated value
is for differentiating the original and stego. images, here �, and ��, are original and stego.
images.
1-bit-steganography in frequency domain (1bsf)
P2
Pi
P4
P3
P1
This novel steganographic schemes DFTMCIAWC based on Discrete Fourier Transformation
(DFT) to authenticate multimedia colour images in frequency domain and two parties can share
secrete data via wireless communication. Authentication is done through embedding secrete
message/image into the transformed frequency components of the source image at message
originating node. The DFT is applied on sub-image block called mask of size 2 x 2 in row major
order where authenticating message/image bit is fabricated within the real frequency component
of each source image byte except the first frequency component of each mask.
2-bits-steganography in frequency domain (2bsf)
This novel technique for Image Authentication in Frequency Domain using Discrete Fourier
Transformation Technique (IAFDDFTT) has been proposed to authenticate a gray level PGM,
TIFF image by embedding a message/image where 2 x 2 submatrix is taken as source matrix from
the image matrix and transform into the frequency domain. Two bits of authenticating
message/image are fabricated within the real part of each pixel, excluding the 1st pixel of each
submatrix where the position is chosen using a hash function. The process is repeated for each
submatrix on row major order to insert authenticating message/image content and 128 bits
Message Digest (MD-5), generated from authenticating message/image. Inverse DFT is
performed to transform the embedded image from frequency to spatial domain as final step of
encoding. In the second steganographic technique which demonstrates the colour image
authentication process in frequency domain based on the Discrete Fourier Transformation (DFT).
Image authentication is done by hiding secrete message/image into the transformed frequency
component of source image. The DFT is applied on sub-image block called mask of size 2 x 2 in
row major order. Secrete message/image bit is fabricated within the transformed real frequency
component of each source image byte except the first frequency component of each mask. Here a
control technique is applied to minimise the noise integration.
3-bits steganography in frequency domain (3bsf)
This novel data embedding technique in frequency domain has been proposed using Discrete
Fourier Transform (DFT) for image authentication and secured message transmission based on
hiding a large volume of data into gray images. Image authentication is done by embedding
message/image in frequency domain by choosing image blocks of size 2 × 2, called mask, from
the source image in row major order and transform it into the frequency domain using DFT.
Three bits of authenticating message/image/message-digest are fabricated within the real parts of
each source image byte except first frequency component of each mask. The dimension of
authenticating image followed by message digest (MD) and the content of authenticating
message/image are also embedded. Inverse DFT (IDFT) is performed on embedded data to
transform embedded frequency component to spatial component. The proposed IATFDDFT
emphasizes on information and image protection against unauthorized access in frequency
domain to achieve a better trade-off between robustness and perceptibility.
The outlines of frequency domain algorithms are stated in sections 1.4.4, 1.4.5 and 1.4.6. All
techniques are implemented using Discrete Fourier Transform (DFT) for spatial to frequency
domain transformation and Inverse Discrete Fourier Transform (IDFT) for frequency to spatial
domain. Comparative study has been made by calculating MSE, PSNR and IF using equation 1.3,
1.4 and 1.5 respectively. The following equations are used DFT and IDFT for domain
transformation. Equation 1.6 and 1.7 are for DFT and IDFT respectively.
( ) ( )∑ ∑−
=
+−−
=
=1
0
21
0
, 1
,M
x
N
vy
M
uxjN
y
eyxfMN
vuFπ
---------------------- (1.6)
( ) ( )∑ ∑−
=
+−
=
=1
0
21
0
, 1
,M
u
N
vy
M
uxjN
v
evuFMN
yxfπ
---------------------- (1.7)
Where u = 0 to M – 1 and v = 0 to N – 1 and x, y are spatial image variable.
Organization of the thesis
Chapter 2 discusses the technique (BLIA/SMTT) and stated results on 1-bit-steganography on
gray images and mask based colour image authentication technique (MDHIAT) is described in
the chapter 3. Chapter 4 and 5 are discusses the techniques of AI/HLVD and IAHLVDSMTTM
for grayscale and colour image authentication respectively using 2-bit-authentication. 3-bits-
steganography techniques FBIA and ATILD for grayscale and colour images are stated in
chapter 6 and 7 respectively. Chapter 8 discusses the technique IAFDDFTT for grayscale image
authentication using 2-bit-steganography in frequency domain and another authentication
technique IATFDDFT discusses and stated result in chapter 9 using 3-bit-steganography.
Chapter 10 and 11 discusses the technique and results for colour image authentication using 1-