A NOVEL METHOD FOR HIDING INFORMATION

ISSN: 2312-7694
Samer et al. / International Journal of Computer and Communication System Engineering (IJCCSE)
107 | P a g e
© 2014, IJCCSE All Rights Reserved Vol. 1 No.03 October 2014 www.ijccse.com
A NOVEL METHOD FOR HIDING INFORMATION Samer Thaaban Abaas Al-Shibley Education College, Kufa University
samir-alshebly@uokufa.edu.iq
Abstract— In this paper, we introduce a new method to hide information in an image, the sequence of hiding message bits in the cover pixels and the number of bits used for hiding information are differ from one block to another and depend on the gray scale values of the pixels in the center of cover image blocks. The proposed system like all steganography system consists of two stages. The first stage used for hiding message by using two keys , the first one used for determining the sequence that will be used in hiding message pixels, while the second key used to select the number of least significant bits in the cover image that will be used in hiding information. The second stage used for extracting and retrieving message information and reconstruct the message image precisely. Keywords: Steganography, hiding information, stego image, cover.
I. INTRODUCTION
Steganography is the art and science of hiding information in a deterministic sequence to prevent any person from detecting the hiding Information without authentication, the secret Information is embedded in a digital file by using a suitable algorithm, there are two types of materials existing in steganography system which are the message and the carrier (cover), Message is the secret Information that should be hidden and carrier is the material that takes the message in it according to steganography algorithm and keys. The file produced after hiding the message in the cover is called stego object that translated from the source of the message to its destination. There are many applications for steganography which are military, diplomatic, and personal applications. There are three related principles that determining the effectiveness of steganography algorithm which are
1- The size of the message file.
2- The difficulty of detecting the message.
3- The difficulty of altering the message by simple changing in the cover file
Steganography can be classified into three types as illustrated in figure (1)
II. ACCORDING TO COVER FILE TYPE
 Text steganography.
 Image steganography.
 Audio steganography.
 Video steganography.
Image Steganography can be classified into three types
a) Least Significant Bits (LSBs):
 Blind hide algorithm.
 Hide seek algorithm.
 Filter first algorithm.
 Battle steg algorithm.
b) Masking and filtering techniques, take a different approach to hiding a message. These methods are effectively similar to paper watermarks, creating markings in an image. This can be achieved for example by modifying the luminance of parts of the image. While masking does change the visible properties of an image, it can be done in such a way that the human eye will not notice the anomalies.
c) Transform Domain techniques utilize an algorithm such as the Discrete Cosine Transformation (DCT) or wavelet transformation to hide information in significant areas of the image.
III. According to the type of the steganography key:
 Pure steganography.
 Secret key steganography.
IV. PROPOSED SYSTEM
In generl,the proposed system as illustrated in figure (2) consist of two steges, the first one is Message hiding stage and the second stage is message extracting from the stego object

ISSN: 2312-7694
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Steganography
Classification according to cover file type
Classification according to how the information has been hidden
Classification according to the type of the key
Line shift
Word shift
Feature
Pure
Secret Key
Public Key
Insertion
Substitution
Generation
Text
Image
Audio
Video
Transformation
Masking and filtering
LSBs
SS
Phase
Parity
LSBs
Echo
Blind hide
Hide seek
Filter first
Battle steg

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Figure (1) classification of steganography systems
Message hiding stage
Figure (2) block diagram of the proposed system
a. message hiding stage
this stage is divided into the following steps:-
1- Divided cover image into non overlap blocks with size (3×3) pixels.
2- Check the three LSBs of the pixel in the center of each block (TLSBS) .
3- Hiding the message in each pixel in the blocks except the centers as illustrated in figure (3) to produce stego object.
figure (3)
1
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7
8
9 Case (1) TLSB = 0 NBITS = 2 Case (2) TLSB = 1 NBITS = 1
9
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3
2
1
3
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1
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Message extracting stage
Image
Message
Divided into non overlap blocks with size (3×3)
Apply inverse proposed hiding algorithm to extract message from stego image
Stego image
(= 0) Hiding in two bits by starting from top left corner
Cover
(Image)
Message (Image)
Divided into non overlap blocks with size (3×3)
Check the value of three LSBs of each pixel in the center of the block
(= 1) Hiding in one bit by starting from top left corner
(= 2) Hiding in two bits by starting from down right corner
(= 3) Hiding in one bit by starting from down right corner
(= 4) Hiding in two bits by starting from down left corner
(= 5) Hiding in one bit by starting from down left corner
(= 6) Hiding in two bits by starting from top right corner
(= 7) Hiding in one bit by starting from top right corner

ISSN: 2312-7694
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Figure (3) the direction of hiding information and number of
bits for eight cases of variable (TLSBS)
Where
NBITS is the number of bits used in hiding information.
TLSB is the value of three least significant bits.
In addition to above operations in hiding stage, hiding
information starting by substituting message bits in cover
blocks with (TLSBS = 0) then in blocks with (TLSBS = 1) and
so on. This make hiding operation progress in random fashion.
If the message pixels are (104, 128…), this mean
(01101000, 10000000, …….), and the cover block is
190
200 210
185 202 207
180 190 200
TLSBS = 2, so case (3) will be applied, Then the numbers are
represented in binary as
202 1 1 0 0 1 0 1 0
Values
Before
hiding
2
LSBs
Before
hiding
2
LSBs
After
hiding
Values
After
hiding
200 1 1 0 0 1 0 0 0 0 1 201
190 1 0 1 1 1 1 1 0 1 0 190
180 1 0 1 1 0 1 0 0 1 0 182
207 1 1 0 0 1 1 1 1 0 0 204
185 1 0 1 1 1 0 0 1 1 0 186
210 1 1 0 1 0 0 1 0 0 0 208
200 1 1 0 0 1 0 0 0 0 0 200
190 1 0 1 1 1 1 1 0 0 0 188
At the end this block becomes
188
200 208
186 202 204
182 190 201
b. Message extracting stage
This stage consist of the following steps
1- Divided stego object image into non overlap blocks
with size (3×3) pixels.
2- Check the three LSBs of the pixel in the center of
each block (TLSBS).
3- Extracting the message in each pixel in the blocks
except the centers as illustrated in figure (3).
For the same block resulted in hiding stage the center of block
(202) represented in binary as
1 1 0 0 1 0 1 0
The variable (TLSBTS= 2), so case 3 will be applied to extract
message bits as follow
201 1 1 0 0 1 0 0 1
190 1 0 1 1 1 1 1 0
182 1 0 1 1 0 1 1 0
204 1 1 0 0 1 1 0 0
186 1 0 1 1 1 0 1 0
208 1 1 0 1 0 0 0 0
200 1 1 0 0 1 0 0 0
188 1 0 1 1 1 1 0 0
Te message bits are ( 01 10 10 00 10 00 00 00 ) that mean
(104, 128)
V. RESULTS
1- The cover image is gray scale image of size
(552×340) pixels, while message is gray scale image
of size (144×144) pixels, the peak signal to noise
ratio is (47) which calculated by applying the
following equation
(1)
1
10 1
0
1
0
2
2
10
[ ( , ) ( , )]
( 1)
log
 




 
 n
r
m
c
peak
g r c I r c
l
SNR
n m
Where, l is the number of gray levels in cover
image.
I(r,c) are the pixels before embedding process in cover
image.
g(r,c) are the pixels after embedding process in stego
image.
n,m are the width and height of cover image
respectively.
Figure (4) result (1) of the proposed system

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a- Original image b- Message c- Stego image 2- The cover image is gray scale image of size (256×384) pixels, while message is gray scale image of size (136×93) pixels, the peak signal to noise ratio is (46) Figure (5) result (2) of the proposed system a- Original image
b - Message
a- Stego image
3-The cover image is gray scale image with size of (256×256) pixels, while the message is gray scale image with size of (102×102) pixels, the peak signal to noise ratio is (45.5) Figure (6) result (3) of the proposed system
a- Original image

ISSN: 2312-7694
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b - Message
b- Stego image
VI. CONCLUSIONS
 The size of message cannot be expected from the size of the cover image because it depends on the values of pixel in the center of the blocks.
 The change in cover image is unnoticeable therefore peak signal to noise ratio in high rate .
 The number of bits used in hiding information change from one block to another, the direction of hiding message bits also change from one block to another, and the blocks are not used in sequential arrange, so information may be hidden in last block before the first one in the same row, these features make this algorithm strong against the attackers.
REFERENCES
[1]- Eric Cole, and Ronald D. Krutz " Hiding in Plain Sight: Steganography and the Art of Covert Communication", Wiley Publishing USA, 2003. [2]- Sabu M Thampi "Information Hiding Techniques: A Tutorial Review" Department of Computer Science & Engineering LBS College of Engineering, Kasaragod Kerala, India, 2004. [3]- Samir K Bandyopadhyay, Debnath Bhattacharyya, Debashis Ganguly, Swarnendu Mukherjeeand Poulami Das "A Tutorial Review on Steganography" ,University of Calcutta ,2008. [4]- Dr.M.Umamaheswari, Prof.S. Sivasubramanian, and S.Pandiarajan "Analysis of Different Steganographic Algorithms for Secured Data Hiding", IJCSNS International Journal of Computer Science and Network Security, 2010. [5]- Shrikant s. khaire, and dr.sanjay l.nalbalwar "Review: Steganography – Bit Plane Complexity Segmentation (BPCS) Technique " International Journal of Engineering Science and Technology, 2010.

A NOVEL METHOD FOR HIDING INFORMATION

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A NOVEL METHOD FOR HIDING INFORMATION