Hl3312951297

Salony Pandey, Prof. Amit.M.Lathigara / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 3, Issue 3, May-Jun 2013, pp.1295-1297
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Hiding Text behind Image for Secure Communication
Salony Pandey1
, Prof. Amit.M.Lathigara2
1
PG Student,RK UNI,Rajkot
2
C.E Dept. R.K UNI Rajkot
Abstract
Steganography is the art of hiding the
fact that communication is taking place, by
hiding information in other information. Many
different carrier file formats can be used, but
digital images are the most popular because of
their frequency on the Internet. For hiding
secret information in images, there exist a large
variety of steganographic techniques some are
more complex than others and all of them have
respective strong and weak points. Different
applications have different requirements of the
steganography technique used. This paper
intends to give an overview of image
steganography, its uses.
I. INTRODUCTION
Steganography is the art and science of
invisible communication. This is accomplished
through hiding information in other information,
thus hiding the existence of the communicated
information. The word steganography is derived
from the Greek words “stegos” meaning “cover”
and “grafia” meaning “writing” [1] defining it as
“covered writing”. In image steganography the
information is hidden exclusively in images. Today
steganography is mostly used on computers with
digital data being the carriers and networks being
the high speed delivery channels. Steganography
differs from cryptography in the sense that where
cryptography focuses on keeping the contents of a
message secret, steganography focuses on keeping
the existence of a message secret [2].
Steganography and cryptography are both ways to
protect information from unwanted parties but
neither technology alone is perfect and can be
compromised. Once the presence of hidden
information is revealed or even suspected, the
purpose of steganography is partly defeated [2].
The strength of steganography can thus be
amplified by combining it with cryptography.
Research in steganography has mainly been driven
by a lack of strength in cryptographic systems.
Many governments have created laws to either
limit the strength of a cryptographic system or to
prohibit it altogether [4], forcing people to study
other methods of secure information transfer.
Businesses have also started to realize the potential
of steganography in communicating trade secrets or
new product information. Avoiding communication
through well-known channels greatly reduces the
risk of information being leaked in transit [5].
Hiding information in a photograph of the company
picnic is less suspicious than communicating an
encrypted file.
II.CATEGORIES OF STEGANOGRAPHY
Almost all digital file formats can be used
for steganography, but the formats that are more
suitable are those with a high degree of
redundancy. Redundancy can be defined as the bits
of an object that provide accuracy far greater than
necessary for the object’s use and display [6]. The
redundant bits of an object are those bits that can
be altered without the alteration being detected
easily [3]. Image and audio files especially comply
with this requirement, while research has also
uncovered other file formats that can be used for
information hiding .Figure 1 shows the four main
categories of file formats that can be used for
steganography.
Hiding information in text is historically the most
important method of steganography. An obvious
method was to hide a secret message in every nth
letter of every word of a text message. It is only
since the beginning of the Text Images
Audio/video Protocol Internet and all the different
digital file formats that is has decreased in
importance [1]. Text steganography using digital
files is not used very often since text files have a
very small amount of redundant data.
Given the proliferation of digital images, especially
on the Internet, and given the large amount of
redundant bits present in the digital representation
of an image, images are the most popular cover
objects for steganography.
To hide information in audio files similar
techniques are used as for image files. One
different technique unique to audio steganography

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is masking, which exploits the properties of the
human ear to hide information unnoticeably. A
faint, but audible, sound becomes inaudible in the
presence of another louder audible sound [1]. This
property creates a channel in which to hide
information. Although nearly equal to images in
steganographic potential, the larger size of
meaningful audio files makes them less popular to
use than images [5].
The term protocol steganography refers to
the technique of embedding information within
messages and network control protocols used in
network transmission [8]. In the layers of the OSI
network model there exist covert channels where
steganography can be used [7]. An example of
where information can be hidden is in the
header of a TCP/IP packet in some fields that are
either optional or are never used. A paper by Ahsan
and Kundur provides more information on this [8].
III. IMAGE STEGANOGRAPHY
PRINCIPAL
IV.IMAGE STEGANOGRAPHY TERMS
• Carrier File – A file which has hidden
information inside of it
• Steganalysis – The process of detecting
hidden information inside of a file.
• Stego-Medium – The medium in which the
information is hidden.
• Redundant Bits – Pieces of information
inside a file which can be overwritten or
altered without damaging the file.
• Payload – The information which is the be
concealed.
V. HIDING A MESSAGE INSIDE
IMAGES
Hiding information inside images is a
popular technique nowadays. An image with a
secret message inside can easily be spread over the
World Wide Web or in news groups. The use of
steganography in newsgroups has been researched
by German steganographic expert Niels Provos,
who created a scanning cluster, which detects the
presence of hidden messages inside images that
were posted on the net. However, after checking
one million images, no hidden messages were
found, so the practical use of steganography still
seems to be limited. To hide a message inside an
image without changing its visible properties, the
cover source can be altered in "noisy" areas with
many color variations, so less attention will be
drawn to the modifications. The most common
methods to make these alterations involve the
usage of the least-significant bit(LSB).
VI. LEAST SIGNIFICANT BIT METHOD
The popular and oldest method for hiding
the message in a digital image is the LSB method.
In LSB method we hide the message in the least
significant bits (LSB’s) of pixel values of an image.
In this method binary equivalent of the secret
message is distributed among the LSBs of each
pixel.
For example data bits 01100101 are tried
to hide into an 8 bit colour image. According to this
technique 8 consecutive pixels from top left corner
of the image are selected. The binary equivalent of
those pixels may be like this:
00100101 11101011 11001010 00100011
11111000 11101111 11001110 11100111
Now each bit of data 01100101 are copied serially
(from left hand side) to the LSB’s of equivalent
binary pattern of pixels, resulting the bit pattern
would become:
00100100 11101011 11001011 00100010
11111000 11101111 11001110 11100111
The problem with this technique is that it is very
vulnerable to attacks such as image compression
and quantization of noise
.
LSB - Uses
• Storing passwords and/or other
confidential information
• Covert communication of sensitive data
• Speculated uses in terrorist activities
• Being widely used to hide and/or transfer
illegal content
VII. REASONS FOR USING DIGITAL
IMAGES
• It is the most widely used medium being
used today
• Takes advantage of our limited visual
perception of colors
• This field is expected to continually grow
as computer graphics power also grows
• Many programs are available to apply
steganography
VIII. IMAGE ATTRIBUTES
• Digital images are made up of pixels

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• The arrangement of pixels make up the
image’s “raster data”
• 8-bit and 24-bit images are common
• The larger the image size, the more
information you can hide. However,
larger images may require compression to
avoid detection
IX. STEGANALYSIS
For hiding information, an equal number
of clever techniques have been designed to detect
the hidden information [9]
. These techniques are
collectively known as ‘steganalysis’. As introduced
earlier, the Laplace formula is one such
steganalytic method. Attacks on steganography can
involve detection and/or destruction of the
embedded message. A stego-only attack is when
only the stego-image is available to be analysed .
A known cover attack is when the original
cover image is also available. It involves
comparing the original cover image with the stego-
image. As hiding information results in alterations
to the properties of a carrier which may result in
some sort of degradation to the carrier. Original
images and stego-images can be analyzed by
looking at colour composition, luminance and pixel
relationships and unusual characteristics can be
detected. If a hidden message is revealed at some
later date the attacker could analyse the stego-
image for future attacks. This is called known
message attack.
The chosen stego attack is used when the
steganography algorithm and the image are known.
A chosen message attack is when the stegoanalyst
generates stego-images using a given
steganography algorithm using a known message.
The purpose is to examine the patterns produced in
the stego images that may point to the use of
certain steganography algorithms. Most
steganographic algorithms embed messages by
replacing carefully selected pixels bits with
message bits.
Any changes to the data associated with
the image through embedding will change the
properties of the image in some way. This process
may create patterns or unusual exaggerated noise.
Two other popular techniques are RS Analysis and
Sample Pairs Analysis. RS Analysis makes small
modifications to the least significant bit plane in an
image then uses these modifications and a
discrimination function to classify groups of pixels.
The counts of the groups based on the
modifications allow the calculation of an estimated
embedding rate. Images that do not contain
steganography often have a natural embedding rate
of up to 3%, whereas images containing hidden
information usually have estimated embedding
rates which accurately reflects the amount of
hidden information. RS Analysis is a special case
of Sample Pairs Analysis, which also uses least
significant bit modifications to help calculate an
estimated embedding rate.
Sample Pairs Analysis utilizes finite state machines
to classify groups of pixels modified by a given
pattern. Both steganalysis techniques are very
accurate at predicting the embedding rate on stego-
images using least significant bit embedding
X.CONCLUSION
Image Steganography as a whole has existed in
many forms throughout much of history.
Lossless compression of images with a great deal
of color variation work best as a cover image to
embed a message. Image Steganography can be
used as beneficial tool for privacy
REFERENCES
[1] Moerland, T., “Steganography and
Steganalysis”, Leiden Institute of
Advanced Computing Science,
www.liacs.nl/home/ tmoerl/privtech.pdf
[2] Wang, H & Wang, S, “Cyber warfare:
Steganography vs. Steganalysis”,
Communications of the ACM, 47:10,
October 2004
[3] Anderson, R.J. & Petitcolas, F.A.P., “On
the limits of steganography”, IEEE
Journal of selected Areas in
Communications, May 1998
[4] Dunbar, B., “Steganographic techniques
and their use in an Open-Systems
environment”, SANS Institute, January
2002
[5] Artz, D., “Digital Steganography: Hiding
Data within Data”, IEEE Internet
Computing Journal, June 2001
[6] Currie, D.L. & Irvine, C.E., “Surmounting
the effects of lossy compression on
Steganography”, 19th
National
Information Systems Security Conference,
1996
[7] Handel, T. & Sandford, M., “Hiding data
in the OSI network model”, Proceedings
of the 1st
International Workshop on
Information Hiding, June 1996
[8] Ahsan, K. & Kundur, D., “Practical Data
hiding in TCP/IP”, Proceedings of the
Workshop on Multimedia Security at ACM
Multimedia, 2002
[9] M. Wu and B. Liu, Multimedia Data
Hiding. New York: Springer-Verlag, 2003

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