Abstract—Least Significant Bit Steganographic techniques are
the most simple and commonly used data hiding techniques using
images as cover files. In LSB Steganographic techniques secret
information bits are replaced with the least significant bits of images
pixels. A number of LSB Steganographic techniques are available. In
this work a new LSB technique is proposed using bit
complementation. 4 of the 8 bits representing pixels are taken as
target bits so as to replace with it the secret data bits or its
complement depending on its matching decision. Bits from 2 to 5 are
taken as the target bits. The first bit is reserved for decision whether
to replace the target bits with the data bits or with the complement of
the data bits. The proposed technique ensures ultimate security of the
secret information and highest data hiding capacity compared to any
of the technique available so far.
Keywords—Steganography, LSB, Security, Image, Complement,
Data hiding
I. INTRODUCTION
TEGANOGRAPHY is a communication technique that
hides the secret information in another information type
[1]. Greek developed the technique of writing secret messages
on wooden tablets and then covering the tables with wax.
Pirate’s legends introduced the technique of tattooing the
shaved heads of their men and when the hair would grow it
will conceal the secret messages. In World War II, Germans
developed a unique technique called microdots [4]. They
printed high quality images to the size of a small dot. In Cold
War the Russian and the Americans used to hide sensors in the
enemy's facilities. These sensors would send data without been
caught [4].
With the expansion of internet and electronic ways of
communication the need for secure communication and
Zakir Khan is with the Department of Information Technology, Hazara
University Mansehra, Pakistan (corresponding author’s phone: +92 323
9029100; e-mail: [email protected]).
Mohsin Shah, is with Optical Engineering, School of Optoelectronics,
Beijing Institute of Technology, China, on leave from the Department of
Information Technology, Hazara University Mansehra, Pakistan (e-mail:
Muhammad Naeem is with is with the Department of Information
Technology, Hazara University Mansehra, Pakistan (e-mail:
Danish Shahzad, is with Department Computer Engineering, Kadir Has
University Istanbul, Turkey (e-mail: [email protected]).
Toqeer Mahmood is with the Department of Computer Engineering,
University of Engineering and Technology Taxila, Pakistan (e-mail:
protection of user’s data is felt. Various cryptographic
techniques are available to protect user data. These
techniques change the form of data so attackers are easily
attracted to it. On the other hand Steganographic techniques
hides user’s data in different file formats such as image,
audio, video, and text to which attackers are not attracted as
they cannot suspect that secret information is passing before
them [3].
A Steganographic system is composed of five
components: a) User secret data; b) Cover file (image,
audio, video, text); c) The resultant stego file; d) Hiding
algorithm and e) Decoding algorithm [2].
The least significant bit (LSB) Steganographic technique
is the simplest and commonly used among different
techniques available in the literature. In LSB technique,
secret information is embedded in the least significant bits
representing pixels or samples of the cover file. All the LSB
techniques available in the literature have their merits and
demerits in terms of payload and perceptibility of the secret
information [1], [5].
The proposed technique achieves highest SNR and
maximum payload compared to any of the available LSB
technique in the literature. We analyze the results by taking
into consideration various image. It is observed that the
proposed technique in terms of the image quality attributes
is well above all the LSB techniques available in literature
so far.
The rest of the paper is arranged as follows: Section II gives
a summary of related work, while Section III explains
proposed technique and section IV concludes the paper.
II. LITERATURE REVIEW
Image LSB steganography is the technique of embedding
secret information bits in the least significant bits of pixels of
an image. Image steganography is classified to the following
type- Transform technique, Distortion technique, LSB
technique, and Statistical technique. A comprehensive survey
of the most recent LSB Steganographic techniques is presented
by Priya Thomson in [5]. Secret data is embedded in the least
significant bits GIF images which is palette based format and
stores image colors in alpha channel or a lookup table [6]. The
data embedding capacity of GIF images is less and is
vulnerable to attacks. Difference expansion technique makes
use of redundancy and embeds 1 bit of secret information in 2
bits of cover image. Producing low visual quality stego images
is the main drawback of this technique [7]. Corners of images
LSB Steganography using Bits
Complementation
Zakir Khan, Mohsin Shah, Dr. Muhammad Naeem, Danish Shehzad, and Toqeer Mahmood
S
Int'l Conf. on Chemical Engineering & Advanced Computational Technologies (ICCEACT’2014) Nov. 24-25, 2014 Pretoria (South Africa)
http://dx.doi.org/10.15242/IIE.E1114029 84
are exploited for secret information bits embedding [8]. As not
enough data bits can be embedded in the corners of images the
capacity of this technique is less. In edge based LSB technique
edges of an image are identified where pixels from their
neighbors are different [9]. Data is embedded in the LSB bits
of pixels present in edges of an image. This technique suffers
from low information hiding capacity. Pixel value differencing
and modulus function is used to embed information bits into
the LSB of images [10]. This technique embeds less
information bits in images. Interpolation technique embeds
more secret information bits in complex areas of images and
less in smooth regions [11]. This technique makes use of
interpolation error to hide data in images. Adaptive edge based
technique uses a pseudo random number generator to select
embedding areas in images [12]. More information bits are
embedded in sharp region compared to smooth regions.
III. PROPOSED TECHNIQUE
In this paper a new Steganographic technique is proposed
for secure data transmission based on data and its
complement mechanism for secret data transfer. This
technique is based on 4 bits data and its complement
enabling to hide 4-bit data in a single pixel of image and
make it unpredictable for the attackers.
First separate least significant bit and make it decision bit of
data recovery. After separating least significant bit take four
bits from data. Now take complement of the data bits, and
compare both data bits and complement of data bits with the
image 4 LSB excluding the decision bit i.e compare with 2-5
LSB of image. Replace image 2-5 bits of a pixel with data or
complement of data which is nearest to the image bits, means
there is minimum difference between the image bits and
replacement bits. If image bits are replaced with data bits than
replace the decision bit with 0 else replace decision bit with 1
as shown in Figure 1.
The reverse process is based on decision bit. First we read
the decision bit if the value of decision bit is 0 then the next 4-
LSB’s i.e from bit # 2 to bit # 5 are the data bits, and if the
decision bit value is 1 it’s means the 4LSB’s i.e from bit # 2 to
bit # 5 are the complement of data bits. So take complement of
4LSB’s and write to the data file. All this procedure is shown
in the Figure 2.
Fig. 1 Data Encoding Process
Int'l Conf. on Chemical Engineering & Advanced Computational Technologies (ICCEACT’2014) Nov. 24-25, 2014 Pretoria (South Africa)
http://dx.doi.org/10.15242/IIE.E1114029 85
Fig. 2 Decoding Process
A. Encoding Process
Step: 1 Read the Data
Step: 2 Read the Image
Step: 3 For Every pixel of Image
Step: 3.1 Read 4LSB’s i.e 2,3,4,5
Step: 3.2 Read a Nibble of Data
Step: 3.3 Get Complement of Data Nibble
Step: 3.4 Compare 4LSB’s with Data Nibble and (Data
Nibble)ʹ
Step: 3.5 Replace 4LSB’s with Nearest One i.e Data
Nibble or (Data Nibble)ʹ
Step: 3.6 if Replacement bit are Data bits
Replace 1LSB with 0
Step: 3.7 else
Replace 1LSB with 1
Step: 4 Write the Stego Image
B. Encoding Process
Step: 1 Read the Stego Image
Step: 2 For Every pixel of Image
Step: 2.1 if decision bit is 0
4LSB’s i.e 2,3,4,5 is data nibble
Step: 2.2 else
Complement of 4LSB’s i.e 2,3,4,5 is data
nibble
Step: 3 write the secret Data to file
C. Example:
The whole Encoding and Decoding process of the proposed
method is illustrated with the help of an example:
Encoding
Suppose we have a pixel 10011011 and data nibble 1001
1st separate the bits of pixel into three parts 100 1101 1
The 100 bits are the most significant bits of pixel
The 1101 are the targeted 4-LSB’s
The last 1 is the least significant bit used as decision bit for
recovery
Now take complement of data nibble i.e. 0110
By comparing the targeted 4-LSB’s with data nibble and the
complement of data nibble
As targeted 4-LSB are near to data nibble so replace the
targeted bits with data bits and replace the decision bit with
0.
So the new pixel will be 100 1001 0
Decoding
Suppose we have a pixel 10010010
1st separate the bits of pixel into three parts 100 1001 0
The 100 bits are the most significant bits of pixel
Read the decision bit
As decision bit is 0
The next 4LSB’s i.e 2, 3, 4, 5 are the data nibble
Int'l Conf. on Chemical Engineering & Advanced Computational Technologies (ICCEACT’2014) Nov. 24-25, 2014 Pretoria (South Africa)
http://dx.doi.org/10.15242/IIE.E1114029 86
IV. CONCLUSION
In this paper a new LSB Steganographic technique is
presented. The presented technique is based on the
complementation and matching of the secret information
nibble. Secret information bits are grouped as nibbles and the
complement of each nibble is found. Each nibble or its
complement is replaced with the bits of each pixel called target
bits. Bit number 2 to 5 are the target bits with which secret
information nibble or its complement is replaced. Bit number
first is used for decision whether to replace information nibble
or its complement. The remaining 3 most significant bits are
lift unchanged. The proposed technique hides 4 bits of
information in every pixel of the cover image. This means that
the proposed technique has a high information hiding capacity.
As it cannot be identified that the bits at positions 2 to 5 are
the bits of information or its complement, hence the proposed
technique keeps high security of the secret information.
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Zakir Khan has done his Bachelor of Computer Science from Hazara
University Mansehra, Pakistan in 2012 and is currently enrolled for his
Master in Computer Science at the Department of Information Technology
Hazara University, Pakistan. He is a skilled programmer and his research
interests include Image processing, Optical fiber communication, and
computer networks.
Mohsin Shah (on leave) is serving as Lecturer at the Department of
Information Technology Hazara University Mansehra, Pakistan. He is
currently pursuing his Ph.D. in Optics from School of Optoelectronics,
Beijing Institute of Technology, China. He completed his B.Sc.
Telecommunication Engineering from University of Engineering and
Technology Peshawar, Pakistan in 2007 and M.Sc. Telecommunication
Engineering from University of Engineering and Technology Taxila, Pakistan
in 2012. Recently he is admitted for his PhD in Optical Engineering at
Beijing Institute of Technology China. He has 2 years of diversified
experience in the field of cellular mobile communication systems. His
research interests include Optics and Photonics, Network Security and Image
Processing.
Muhammad Naeem is serving as Lecturer at the Department of
Information Technology Hazara University Mansehra, Pakistan. He got his
Ph.D. from University of Leicester, UK in 2012. His research interests
include Software Product Lines, Requirements Engineering, Steganography,
and Computational Mathematics. He is also interested in formal framework
like Linear Logic and Proportional Logic.
Danish Shahzad is serving as Research Assistant at Department of
Computer Engineering, Kadir Has University Istanbul, Turkey. He has done
his MS in Computer Science in 2014 from Hazara University Mansehra,
Pakistan. He completed his BS in Telecommunication in 2010 from Comsats
Institue of Information Technology. His research interests include Mobile
Adhoc Networks, Network security, Parallel programming and Hybrid
programming.
Toqeer Mahmood is currently serving as Programmer at University of
Engineering and Technology Taxila, Pakistan. He completed his MS
Computer Engineering in 2010 from Center for Advanced Studies in
Engineering (CASE) Islamabad, Pakistan. He is currently pursuing his Ph.D.
in Image Processing from University of Engineering and Technology Taxila,
Pakistan. His research interests include Image Processing, Computer vision,
Computer Networks and Numerical Techniques.
Int'l Conf. on Chemical Engineering & Advanced Computational Technologies (ICCEACT’2014) Nov. 24-25, 2014 Pretoria (South Africa)
http://dx.doi.org/10.15242/IIE.E1114029 87