25-08-2017, 09:32 PM
A Comparative Analysis of Image Steganography
[attachment=25443]
ABSTRACT
Digital communication has become an essential part of
infrastructure now-a-days, a lot of applications are Internetbased
and in some cases it is desired that the communication be
made secret. Two techniques are available to achieve this goal:
cryptography and steganography. In this paper, various digital
steganographic techniques are implemented which are capable
of producing a secret-embedded image that is indistinguishable
from the original image to the human eye. A comparative
analysis is made to demonstrate the effectiveness of the proposed
methods. The effectiveness of the proposed methods has been
estimated by computing Mean square error (MSE) and Peak
Signal to Noise Ratio (PSNR).
Categories and Subject Descriptors
D.2.11 Information hiding
D.4.6 Security and Protection
General Terms
Security
Keywords
LSB Steganography, Information hiding, Inverted Pattern
Approach, Pixel value differencing, Steganography.
1. INTRODUCTION
Internet has becomes essential the most effective and fastest
media for communication. Albeit, it is susceptible to face many
problems such copyright, hacking, eavesdropping etc. Hence the
need for secret communication is required. Cryptography [4, 6,
11] and Steganography [1-3, 5, 7 - 19] are the two fields
available for data security. Cryptography is a technique in which
the data is scrambled in an unintelligent gibberish fashion so that
it becomes difficult for any malicious user to extract the original
message. Only the desired recipient will be having the code for
decryption and will be able to extract messages. Cryptography
has helped a great deal in data security but it has some
disadvantages. The encrypted data will arouse suspicion to
malicious users and there is a possibility of it being decrypted or
being suppressed. Hence the intended information might not
reach its destination effectively. The disadvantages of
Cryptography have lead to the development of Steganography.
In recent years, enormous research efforts have been invested in
the development of digital image steganographic techniques[].
The major goal of steganography is to enhance communication
security by inserting secret message into the digital image,
modifying the nonessential pixels of the image [ ]. The image
after the embedding of the secret message, so-called stego-image,
is then sent to the receiver through a public channel. In the
transmission process, the public channel may be intentionally
monitored by some opponent who tries to prevent the message
from being successfully sent and received. The opponent may
randomly attack the stego-image if he/she doubts the stego-image
carries any secret message because the appearance of the stegoimage
shows obvious artifacts of hiding effect. For this reason,
an ideal steganography scheme, to keep the stego-image from
drawing attention from the opponent, should maintain an
imperceptible stego-image quality. That is to say, if there are
more similarities between the cover image and the stego-image,
it will be harder for an attacker to find out that the stego-image
has important secret data hidden inside it . This way, the secret
data is more likely to travel from the sender to the receiver safe
and sound. For the past decade, many steganographic techniques
for still images have been presented [1-3, 5, 7 - 19] both in
spatial and frequency domains. A simple and well known
approach is directly hiding secret data into the least-significant
bit (LSB) of each pixel in an image.
2. Review on literature
2.1 LSB Substitution Method [5]
The most well-known steganographic technique in the data
hiding field is least-significant-bits (LSBs) substitution. This
method embeds the fixed-length secret bits in the same fixedlength
LSBs of pixels. Although this technique is simple, it
generally causes noticeable distortion when the number of
embedded bits for each pixel exceeds three. Several adaptive
methods for steganography have been proposed to reduce the
distortion caused by LSBs substitution. For example, adaptive
methods vary the number of embedded bits in each pixel, and
they possess better image quality than other methods using only
simple LSBs substitution. However, this is achieved at the cost
of a reduction in the embedding capacity.
2.2 Optimum Pixel Adjustment Procedure [5]
The proposed Optimal Pixel adjustment Procedure (OPAP)
reduces the distortion caused by the LSB substitution method. In
OPAP method the pixel value is adjusted after the hiding of the
secret data is done to improve the quality of the stego image
without disturbing the data hidden.
2.2.1 Procedure for hiding:
• First a few least significant bits are substituted with the data
to be hidden.
• Then in the pixel, the bits before the hidden bits are
adjusted suitably if necessary to give less error.
• Let n LSBs be substituted in each pixel.
• Let d= decimal value of the pixel after the substitution.
• d1 = decimal value of last n bits of the pixel.
• d2 = decimal value of n bits hidden in that pixel.
International Journal of Computer Applications (0975 – 8887)
Volume 2 – No.3, May 2010
42
• If(d1~d2)<=(2^n)/2
then no adjustment is made in
that pixel.
Else
If(d1<d2)
d = d – 2^n .
If(d1>d2)
d = d + 2^n .
This d is converted to binary and written back to pixel.
2.2.2 Retrieval:
The retrieval follows the extraction of the least significant
bits(LSB) as hiding is done using simple LSB substitution.
2.2.3 Advantages:
1. Simple methodology.
2. Easy retrieval.
3. Improved stego-image quality than LSB substitution.
2.3 Inverted Pattern Approach (IP)[17]
This inverted pattern (IP) LSB substitution approach uses the
idea of processing secret messages prior to embedding. In this
method each section of secret images is determined to be
inverted or not inverted before it is embedded. In addition, the
bits which are used to record the transformation are treated as
secret keys or extra data to be re-embedded.
[attachment=25443]
ABSTRACT
Digital communication has become an essential part of
infrastructure now-a-days, a lot of applications are Internetbased
and in some cases it is desired that the communication be
made secret. Two techniques are available to achieve this goal:
cryptography and steganography. In this paper, various digital
steganographic techniques are implemented which are capable
of producing a secret-embedded image that is indistinguishable
from the original image to the human eye. A comparative
analysis is made to demonstrate the effectiveness of the proposed
methods. The effectiveness of the proposed methods has been
estimated by computing Mean square error (MSE) and Peak
Signal to Noise Ratio (PSNR).
Categories and Subject Descriptors
D.2.11 Information hiding
D.4.6 Security and Protection
General Terms
Security
Keywords
LSB Steganography, Information hiding, Inverted Pattern
Approach, Pixel value differencing, Steganography.
1. INTRODUCTION
Internet has becomes essential the most effective and fastest
media for communication. Albeit, it is susceptible to face many
problems such copyright, hacking, eavesdropping etc. Hence the
need for secret communication is required. Cryptography [4, 6,
11] and Steganography [1-3, 5, 7 - 19] are the two fields
available for data security. Cryptography is a technique in which
the data is scrambled in an unintelligent gibberish fashion so that
it becomes difficult for any malicious user to extract the original
message. Only the desired recipient will be having the code for
decryption and will be able to extract messages. Cryptography
has helped a great deal in data security but it has some
disadvantages. The encrypted data will arouse suspicion to
malicious users and there is a possibility of it being decrypted or
being suppressed. Hence the intended information might not
reach its destination effectively. The disadvantages of
Cryptography have lead to the development of Steganography.
In recent years, enormous research efforts have been invested in
the development of digital image steganographic techniques[].
The major goal of steganography is to enhance communication
security by inserting secret message into the digital image,
modifying the nonessential pixels of the image [ ]. The image
after the embedding of the secret message, so-called stego-image,
is then sent to the receiver through a public channel. In the
transmission process, the public channel may be intentionally
monitored by some opponent who tries to prevent the message
from being successfully sent and received. The opponent may
randomly attack the stego-image if he/she doubts the stego-image
carries any secret message because the appearance of the stegoimage
shows obvious artifacts of hiding effect. For this reason,
an ideal steganography scheme, to keep the stego-image from
drawing attention from the opponent, should maintain an
imperceptible stego-image quality. That is to say, if there are
more similarities between the cover image and the stego-image,
it will be harder for an attacker to find out that the stego-image
has important secret data hidden inside it . This way, the secret
data is more likely to travel from the sender to the receiver safe
and sound. For the past decade, many steganographic techniques
for still images have been presented [1-3, 5, 7 - 19] both in
spatial and frequency domains. A simple and well known
approach is directly hiding secret data into the least-significant
bit (LSB) of each pixel in an image.
2. Review on literature
2.1 LSB Substitution Method [5]
The most well-known steganographic technique in the data
hiding field is least-significant-bits (LSBs) substitution. This
method embeds the fixed-length secret bits in the same fixedlength
LSBs of pixels. Although this technique is simple, it
generally causes noticeable distortion when the number of
embedded bits for each pixel exceeds three. Several adaptive
methods for steganography have been proposed to reduce the
distortion caused by LSBs substitution. For example, adaptive
methods vary the number of embedded bits in each pixel, and
they possess better image quality than other methods using only
simple LSBs substitution. However, this is achieved at the cost
of a reduction in the embedding capacity.
2.2 Optimum Pixel Adjustment Procedure [5]
The proposed Optimal Pixel adjustment Procedure (OPAP)
reduces the distortion caused by the LSB substitution method. In
OPAP method the pixel value is adjusted after the hiding of the
secret data is done to improve the quality of the stego image
without disturbing the data hidden.
2.2.1 Procedure for hiding:
• First a few least significant bits are substituted with the data
to be hidden.
• Then in the pixel, the bits before the hidden bits are
adjusted suitably if necessary to give less error.
• Let n LSBs be substituted in each pixel.
• Let d= decimal value of the pixel after the substitution.
• d1 = decimal value of last n bits of the pixel.
• d2 = decimal value of n bits hidden in that pixel.
International Journal of Computer Applications (0975 – 8887)
Volume 2 – No.3, May 2010
42
• If(d1~d2)<=(2^n)/2
then no adjustment is made in
that pixel.
Else
If(d1<d2)
d = d – 2^n .
If(d1>d2)
d = d + 2^n .
This d is converted to binary and written back to pixel.
2.2.2 Retrieval:
The retrieval follows the extraction of the least significant
bits(LSB) as hiding is done using simple LSB substitution.
2.2.3 Advantages:
1. Simple methodology.
2. Easy retrieval.
3. Improved stego-image quality than LSB substitution.
2.3 Inverted Pattern Approach (IP)[17]
This inverted pattern (IP) LSB substitution approach uses the
idea of processing secret messages prior to embedding. In this
method each section of secret images is determined to be
inverted or not inverted before it is embedded. In addition, the
bits which are used to record the transformation are treated as
secret keys or extra data to be re-embedded.