Improved LSB Steganograhy Technique for grayscale and RGB images

Raju Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 10( Part - 2), October 2014, pp.36-38
www.ijera.com 36 | P a g e
Improved LSB Steganograhy Technique for grayscale and RGB
images
Raju*, Mohit Dhanda**
*(Department of Eletronics & Communication, GNI Mullana, Mullana.)
** (Department of Eletronics & Communication, GNI Mullana, Mullana)
ABSTRACT
A number of techniques are there to converse securely. Encryption and cryptography are enabling us
to have a secure conversation. To protect privacy and communicate in an undetectable way it is
required to use some steganography technique. This is to hide messages in some other media
generally called cover object. In todays digital world where images are a common means of
information sharing, most of the steganography techniques use digital images as a carrier for hiding
message. In this paper a LSB based technique is proposed for steganograpgy. This technique is
different from standard LSB technique that along with message hidden in LSB bits a part of message
also resides at other selective bits using a key. The method is developed to increase the payload
capacity and make detection impossible.
Keywords – LSB, peak signal-to-noise ratio, (PSNR), Steganography, Steganalysis, stegokey.
I. INTRODUCTION
Hiding sensitive information within usual
communications is an art termed 'Steganography'. It
is one of the fundamental ways in which information
can be kept confidential. For instance, by hiding
covert messages within other, messages, the chance
of the communication being detected is reduced. The
original message is usually encrypted and then
hidden within a carrier text, image or other file,
producing the stego-text or hidden data. It should be
noted that the main goal of steganography is to
communicate securely in a completely undetectable
manner [1]. Steganography also plays a major role in
the associated technology of digital image
watermarking. Images are the most widespread
carrier medium [2]. Here, a stego tool modifies data
in such a way that the image is still visible through
an applied watermark, but there is no way to remove
this watermark without destroying the image. When
the message is hidden in the carrier a stego-carrier is
formed for example a stego-image. Hopefully it will
be perceived to be as close as possible to the original
carrier or cover image by the human senses. The
sender (or embedder) embeds the secret message to
be sent into a graphic file (the cover image or the
carrier). This results in the production of what is
called a stego-image. Additional secret data may be
needed in the hiding process e.g., a stegokey[4,5].
Cryptography and steganography can be used
together. As cryptography only transforms the data
into gibberish form and transmits it, it tends to
attract the intruders attention. On the other hand
steganography made the task of the intruder even
more difficult by hiding the very existence of the
secret data. However, steganography could be a
failure even if the presence of secret data is detected.
Thus to enhance the security of communications over
covert channels, it is proposed to first encrypt the
secret data using a suitable encryption algorithm,
compress it and then embed it into a cover using an
appropriate steganographic method[6]. If compressed
the message will take up far less space in the carrier
and will minimize the information to be sent. The
random looking message which would result from
encryption and compression would also be easier to
hide than a message with a high degree of regularity.
Therefore encryption and compression are
recommended in conjunction with steganography [7].
One of the earliest methods to discuss digital
steganography is credited to Kurak and Mc Hugh
[8], who proposed a method which resembles
embedding into the 4 LSB,s (least significant bits).
Miaou et al. [9] present an LSB embedding
technique for electronic patient records. Nirinjan and
Anand [10] and Li et al. [11] also discuss patient data
concealment in digital images. This paper proposes
an improved LSB(least Significant bit) based
Steganography technique for images imparting better
information security. It presents an embedding
algorithm for hiding encrypted messages in pixel
locations in LSB and some selected bit positions
determined by a key. The encryption and
compression are eliminated in this scheme. The
RESEARCH ARTICLE OPEN ACCESS

proposed approach is to achieve a better payload
capacity and PSNR value.
II. METHODOLOGY
Steganography involves hiding data in an covert
message and doing it in such a way that it is difficult
for an opponent to detect and difficult to remove.
Least Significant Bit (LSB) embedding is a simple
strategy to implement steganography.
Figure :-1 image steganography process
Like all steganographic methods shown in figure-1 it
embeds the data into the cover so that it cannot be
detected by a casual observer. The technique works
by replacing some of the information in a given pixel
with information from the data in the image. While it
is possible to embed data into an image on any bit-
plane, LSB embedding is performed on the least
significant bit(s). This minimizes the variation in
colors that the embedding creates. This schemes
works for grayscale as well as RGB images. For
example, embedding into the least significant bit
changes the color value by one. Using higher order
bits for embedding message distorts the image to a
greater extent thus loosing the purpose. In case
embedding is performed on the least significant
pixel,it will increase the the likelihood of detection.
In a LSB embedding, some information is always lost
from the cover image. This is an effect of embedding
directly into a pixel. LSB algorithms have a choice
about how they embed that data to hide. They can
embed losslessly, preserving all information about
the data, or the data may be generalized so that it
takes up less space. Digital images are represented as
arrays of pixel values. A pixel is a point of an image.
For a grayscale image there exists only one matrix
containing grayscale level values for each pixel of
image. When dealing with the RGB images there are
three matrics each for red(R), green(G) and blue(B)
colors. Capacity of RGB image is therefore high as a
large number of LSB positions are present for
embedding data. The numeric value of each pixel is
stored in bytes and represents a digital color. Each of
the bytes defines the amount of light intensity in each
of the primary colors: red, green, and blue (RGB)
and can hold values from 0 to 255 (values which can
be stored in 8 bits 28
). For example, 255 for the red
value and 0 for the blue and green will render the
color red. Other values close to 255 for the red
component and 0s for the blue and green will also
render a shade of red which may appear to be the
same color to the human eye.
The proposed algorithm uses the LSB
locations in the image along with some predefined bit
positions in image. The predefined bit locations are
decided by a digital key. This key is only known to
the sender and the receiver. The key embeds the
information at specific locations. To retrieve the
message at receiver end this key is again required. In
standard LSB staganography where the key is used
only for extracting the message in our algorithm this
key performs two operations i.e. retrieving the
message in LSB bits along with the data hidden in
specific locations other than LSB positions.
Figure:-2 flowchart for the proposed protocol.
The key is actually a combination of two keys one
part belongs to LSB data extraction and the other
required to extract data from specific bit locations.
III. RESULT & CONCLUSION
In LSB based steganography LSB positions can
be used for hiding information. It is easy for any
eavesdropper to corrupt the data by just manipulating
the LSB in pixels values. In this proposed method as
selective bit postions definded by key and LSB are
used for hiding data. The key is selected in a way to
optimize the PSNR value. It becomes much difficult
to detect and extact data. Along with this the payload
capacity is also increased.

REFERENCES
Journal Papers:
[1.] Ismail Avcibas, Nasir Memon, and Bulent
Sankur, February 2003, " Steganalysis Using
Image Quality Metrics",IEEE Transaction on
Image Processing , 12(2).
[2.] Westfield Andreas, Pfitzmann Andreas (1999
October ) Attacks on steganographic systems.
Third International Workshop, IH_99
Dresden Germany, Proceedings, Computer
Science 1768, pp 61–76.
[3.] Johnson Neil F, Zoran Duric, Sushil Jajodia
(2001) information hiding, and watermarking
attacks & countermeasures. Kluwer.
[4.] Pfitzmann Birgit (1996, May–June)
Information hiding terminology. First
International Workshop, Cambridge, UK,
Proceedings, Computer Science 1174, pp
347–350.
[5.] Zollner J, Federrath H, Klimant H, Pfitzmann
A, Piotraschke R, Westfeld A, Wicke G,
Wolf G (1998, April) Modelling the security
of steganographic systems, Information
Hiding, 2nd
International Workshop, IH_98
Portland, Oregon, Computer Science 1525,
pp 344–354.
[6.] Aisha Fernandes and W. Jeberson, “Covert
communication techniques in the digital
world” Proc. Of the International conference
[7.] Fridrich Jiri (1999), A new steganographic
method for palette-based images. Center for
Intelligent Systems, SUNY Binghamton,
Binghamton, New York. IS&T_s PICS
Conference, pp 285–289.
[8.] C. Kurak, J. McHugh, A cautionary note on
image downgrading, in: Proceedings of the
IEEE 8th Annual Computer Security
Applications Conference, 30 November–4
December, 1992, pp. 153–159.
[9.] S. Miaou, C. Hsu, Y. Tsai, H. Chao, A secure
data hiding technique with heterogeneous
data-combining capability for electronic
patient records, in: Proceedings of the IEEE
22nd Annual EMBS International
Conference, Chicago, USA, July 23–28,
2000, pp. 280–283.
[10.] U.C. Nirinjan, D. Anand, Watermarking
medical images with patient information, in:
Proceedings of the 20th Annual International
Conference of the IEEE Engineering in
Medicine and Biolog Society, Hong Kong,
China, 29 October–1 November 1998, pp.
703–706

Improved LSB Steganograhy Technique for grayscale and RGB images

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