A- Review On Image Steganography

IJIRST –International Journal for Innovative Research in Science & Technology| Volume 2 | Issue 02 | July 2015
ISSN (online): 2349-6010
All rights reserved by www.ijirst.org 243
Image Steganography Techniques: A Review
Mamta Yadav Amita Dhankhar
M. Tech. Scholar Assistant Professor
UIET, MD University Rohtak, Haryana UIET, MD University Rohtak, Haryana
Abstract
Steganography is an important area of research in recent years. Steganography usually deals with the ways of hiding the
existence of the communicated data in such a way that it remains confidential. Steganography is used some cover media like
image file, audio file, video file, text file to hide the data. In image steganography, secrecy is achieved by embedding data into
cover image and generating a stego-image. Bits of information are placed in pixel values of image so that intruder cannot find
out where data is hidden. There are different types of steganography techniques each have their strengths and weaknesses. In this
paper, we review the different technique of Image steganography - LSB, PVD (least significant bit, pixel value differencing), PIT
(pixel indicator technique), of Image steganography techniques - LSB, PVD (least significant bit, pixel value differencing), PIT
(pixel indicator technique),
Keywords: LSB, PVD, edge, PIT, Steganography, Stego-image, cover-image
_______________________________________________________________________________________________________
I. INTRODUCTION
Two techniques are available to those wishing to transmit secrets using unprotected communications media. One is
cryptography, where the secret is scrambled and can be reconstituted only by the holder of a key. When cryptography is used, the
fact that the secret was transmitted is observable by anyone. The second method is steganography. The word steganography in
Greek means “Covered Writing”. Steganography is the art of information hidden into cover media. Cover media can be a text, or
an image, an audio or video etc.
Main objective of steganography is to communicate securely in such a way that the true message is not visible to the observer.
Today steganography is mostly used on computer with digital data being the carriers and networks being the high speed delivery
channel. Most steganographic utilities hide information inside image, as it is relatively easy to implement. Images are mostly
used in the process or of steganoraphy because it is hard to break.
During the process of hiding the information three factors must be considered that are capacity it includes amount of
information that can be hidden in the cover medium. Security implies to detect hidden information and Robustness to the amount
of modification the stego medium can withstand before an adversary can destroy hidden information.
The importance of steganography lies in the fact that it hides the very existence of the secret it is protecting. Attackers are
threats because they attempt to damage or gain access to assets by taking advantage of these asset‟s vulnerabilities.
Steganography makes the job of the attacker more difficult because the very existence of the asset is hidden. The importance of
steganography in maintaining confidentiality can be illustrated with a simple example. Imagine two coworkers, Alice and Bob,
are communicating with each other over the internet. Eve, an attacker, has access to this communication link, so she eavesdrops
on Alice and Bob‟s communications. If Alice is asking Bob if he is free for lunch, then Alice probably does not mind if Eve
reads this message. Thus, Alice can send her query to Bob along the communication link in plain text. However, if Alice is
sending Bob confidential information, such as specifications for their company‟s latest project, then she probably does not want
Eve to be able to read these messages. Therefore, Alice will likely encrypt her messages. A problem arises because the encrypted
text is likely garbled, nonsensical data. Thus, Eve, even though she cannot read the encrypted messages, will know that Alice has
a secret that she is sending to Bob. Eve can then take the encrypted message and attempt to crack it. This is a very real problem
because as computational power increases, encryption is becoming easier to break. However, if Alice uses steganography, and
hides her secret message in a generic image file, then she can transmit her secret message to Bob without evoking Eve‟s
suspicion. For instance, Alice can hide her secret message in a picture of her garden. She can then send the image, with the secret
message hidden inside it, to Bob. Eve will think Alice is just sending Bob a harmless picture, so she will ignore that
communication between Alice and Bob. Thus, Alice and Bob defeat Eve.
Fig. 1: Block diagram for steganography

(IJIRST/ Volume 2 / Issue 02/ 041)
Information can be hidden in many different ways. In order to hide information, straight message insertion may encode every
bit of information in the cover data or it may selectively embed messages in noisy areas that draw less attention. Messages may
also be scattered randomly throughout the cover data. There are a number of ways to hide information; the most common
methods are the least significant bit (LSB) insertion, masking and filtering and algorithms and transformations.
This paper describes different technique used in image steganography, performance, analysis & comparison on each technique.
II. RELATED WORK
Neil F. Johnson,Sushil jajodia et. Al[ 1] , They discuss different techniques of steganography and file compression, masking &
filtering techniques.
Mamta janesa, parvinder sing sandhu et al[3] ,They discuss the design of a roboust image stegano graphy technique based on
LSB insertion & RSA encryption technique.
Piyush marwaha, paresh marwaha[4], They propose the concept of multiple cryptography where the data will be encrypted
into a cipher & the cipher will be hidden into a multimedia image file in encrypted formal, visual steganography algorithm will
be used to hide the encrypted data.
Feng Pan, Jun Li et al[7] ,They present an image steganography method which utilize horizontal pixel & verticle pixel
difference,in the horizontal direction they use high quality model function method for two pair of pixel embed message they use
PVD method. Pfitzmann & westfield[8],They proposed a particle algorithm for embedding JPEG image that would provide high
steganographic capacity without sacrificing security.
Ming.chen, z.Ru.et al[9] , They have explain many stegnography tools which are capable of hiding data with an image. These
tools can be classified into five category on their algoritham i.e are spatial domain based tools, transform domain based tools,
document based tools, file structure based tools, video compress encoding and spread spectrum techniques.
Hassan mathkour, Btool Ai.sadoon et.[ 10] , They discussed several steganography techniques with an emphasis on image
steganography they list a set of criteria to look into the strength & weaknesses of presented techniques. They also discussed &
compared various steganography tools and implemented a tool exemplifying its process.
Ge Huayong, Huang Mingsheng et. Al, [11] they illustrate concept and priniciple of steganography and steganalysis, spatial
domain and transform domain embedding method are generalized. Then the performance specification of image steganography is
discussed.
Sueed sarreshtedari & shahrokh Ghaemmaghami, [12] they proposed steganography algorithm works on the wavelet transform
coefficients of the original image to embed the secret data.
Krishna Nand Chaturvedi and Amit Doeger[13] proposed an approach for hiding data using lsb on edges of a gray scale cover
images.
Techniques of Image Steganography
A.
We have studied the following techniques of image steganography in our paper:
LSB Method
1)
The popular and oldest method for hiding the message in a digital image is the LSB method [14]. 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 color image. According to this technique 8 consecutive pixels from
top left corner of the image are selected. The binary equivalent of those pixels may b 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.
a) Advantages of LSB
1) Less suspicious to human eyes.
2) Simple to implement and many techniques uses this method.
3) High perceptual transparency.
4) 100% chances of insertion.
b) Disadvantages of LSB
1) Three weakness- Robustness, Tamper and Resistance.
2) Extremely sensitive to any kind of filtering.
3) Scaling, Rotation, Cropping, adding extra noise lead to destroy the secret message.

PVD Method
2)
The pixel value differencing (PVD) method proposed by Wu and Tsai [15] can successfully provide both high embedding
capacity and outstanding imperceptibility for the stego-image. The pixel value differencing (PVD) method segments the cover
image into non overlapping blocks containing two connecting pixels and modifies the pixel difference in each block (pair) for
data embedding. All possible difference values are classified into a number of ranges. A larger difference in the original pixel
values allows a greater modification.
Kim, Jung and Yoo [16] proposed A high capacity data hiding using PVD and LSB Replacement Method. This method
calculates the difference value between two consecutive pixels. The LSB substitution method is used when the difference value
is small (i.e smooth areas) and PVD is used when it is large (i.e edge areas) of cover image pixels. The pixels belong to the edge
areas could embed more data than the smooth area of image thus LSB substitution is used to embed more data on smooth area
without distortion to the human visual system. This method is useful for the grayscale images.
Parity Checker Method
3)
In this method, Rajkumar et al [17] gives the concept of odd and even parity. According to this method, 0 can be inserted at a
pixel location if that pixel has odd parity i.e. the number of 1‟s in the binary value of the pixel should be odd. Similarly, 1 can be
inserted at a pixel location if that pixel has even parity i.e. the number of 1‟s in the binary value of pixel should be even. If the
corresponding parity does not exist at a pixel location either for 0 or 1, then we make corresponding parity at that pixel location
(odd parity for 0 and even parity for 1) by adding or subtracting 1 to the pixel location such that the change in the image quality
should not be visible to the human visual system (HVS). For Retrieval of message, again we used the parity checker. If odd
parity is present at the selected location then, „0„ is message bit, else message bit is „1„. Retrieval process was repeated for all
locations where message bits were hidden. In this way, we retrieved the message bits from all the locations where the message
bit were inserted.
Edge based Method
4)
Yang, Weng, Wang (2008) [18] proposed the new adaptive LSB technique using Pixel Value differencing with spatial LSB
domain technique. It gives high embedding capacity and imperceptible Stego image. This method is used to distinguish between
edge areas and smooth areas. The edge areasare used for the higher embedding capacity for data hiding .This technique comes
under the spatialdomain image processing and this method applied on grayscale images. The quality of stego imagescalculated
from the peak signal to noise ratio (PSNR).
PIT Method
5)
Adnan Abdul-Aziz Gutub[19] proposed a new improved technique Pixel indicator that takes the advantage of the 24 bits in each
pixel in the RGB images using the two least significant bits of one channel to indicate existence of data in the other two
channels. The technique uses least two significant bits of one of the channels Red, Green or Blue as an indicator of secret data
existence in the other two channels. The indicator channel is chosen in sequence from R, G and B, i.e. RGB, RBG, GBR, GRB,
BRG and BGR. However the indicator LSB bits are naturally available random, based on image profile and its properties. The
stego method does not depend on a separate key to take out the key management overhead. Instead, it is using the size of the
secret data as selection criteria for the first indicator channel to insert security randomness.
6th, 7th Bit Method
6)
Parvinder et al [20] obtained an algorithm to hide the message in 6th and 7th bit of pixel value. Here instead of LSB bits 6th and
7th bit of pixel values are used to hide the secret data within an image. This novel proposed method overcomes the all
disadvantages of LSB insertion method .However it has its own disadvantage that is the chance that the message bit will be
inserted at pseudorandom location at first instance is less as compared to LSB.
6th, 7th & 8th Bit Method
7)
Rajkumar et al [21] proposed a novel approach to hide the data 6th, 7th and 8th bit of pixel values. In this method 6th, 7th
and 8th
bits of the image pixels are used to hide the message.
Since this method involves 8th bit for hiding the message, intruder can easily change 8th bit of all image pixels and this may
result in the loss of message. To avoid this, time factor has been introduced, i.e. at some time t1, sender sends the cover object
with message and at some other time t2 sender sends the cover object without message. Sender and recipient agree on this time
factor initially before starting any communication. The advantage of introducing time factor (slot) is that if least significant bits
of all pixels are changed by the intruder even then the message can be retrieved by comparing the two cover objects, i.e. one
containing the message and the other not containing the message.
III. APPLICATIONS OF STEGANOGRAPHY
There are various applications in steganography; it varies among the user requirements such as copyright control, secret
communication, smart ID‟s, tamper proofing etc.
Copyright Control
A.
Inside an image, secret copyright information is embedded. This is achieved by watermarking which is the complex structure so
that the intruder cannot identify the copyright information. There are various methods available to find the watermarking. It is
achieved by statistical, correlation, similarity check. Watermarking is used to protect the copyright information.

Secret Communication
B.
In many situations, transmitting a cryptographic message draws unwanted attention. The use of cryptographic technology may be
restricted or forbidden by law. However, the used steganography does not advertise covert communication and therefore, avoid
scrutiny of the sender, message and recipient.
Tamper Proofing
C.
The objective of tamper-proofing is to answer the question, “Has this image been modified?” Tamper-proofing techniques are
related, but distinct from the other data-hiding technologies. What differentiates them is the degree to which information is
secured from the host signal. Most data-hiding techniques attempt to secure data in the face of all modifications. Tamper-
proofing techniques must be resilient to small modifications (e.g., cropping, tone scale or gamma correction for images or
balance or equalization for sounds) but not to large modifications (e.g., removing or inserting people from an image or taking
words out of context in an audio recording [24].
Digital Watermark
D.
The objective of a digital watermark is to place an indelible mark on an image. Usually, this means encoding only a handful of
bits, sometimes as few as one. This “signature” could be used as a means of tracing the distribution of images for an on-line
news service and for photographers who are selling their work for digital publication. One could build a digital camera that
places a watermark on every photograph it takes. Theoretically, this would allow photographers to employ a “web-searching
agent” to locate sites where their photographs appear [21].
Smart Id’s:
E.
In smart ID‟s the information about the person is embedded into their image for confidential information. For an organization,
the authentication of the resources is accessed by the people. So identifying the theft related to prevention of crimes.
IV. ANALYZING TECHNIQUES OF STEGO IMAGE AND COVER MEDIA
For measuring the quality of reconstructed image that is stegao image as compared to the original image, the metric needs to be
define[27]. There are three common error metrics used for estimating noise on images are RMSE, PSNR, and NCC.
PSNR
A.
The PSNR (Peak Signal to Noise Ratio) measures the similarity between two images (how two images are close to each other).
Peak Signal to Noise Ratio (PSNR): The PSNR is evaluated in decibels and is inversely proportional the Mean Squared Error. It
is given by the equation:
 
2
10
255
10log
PSNR
MSE
 
  
 
where:
I is the dynamic range of pixel values, or the maximum value that a pixel can take, for 8-bit images: I=255.
MSE is the mean square error.
RMSE
B.
The Root mean square error measures the difference between these two images. Since the computing of these two metrics is very
easy and fast, they are widely-used and very popular [13].
 
 
2 2
2
1 1 1
1
( )
N M n
ij ij i
i j i
RMSE X Y X X
N M   
  

 
Here,
N, is the number of rows in the cover image.
M, is the number of column in the cover image
Xij, intensity of pixel ij in cover image
Yij, intensity of pixel ij in stego image
Assuming pixel values in the range [0,255], the following observations are mentioned as:
RMSE of zero which means an identical image results in infinite or undefined PSNR
RMSE of 255 result in PSNR of zero
RMSE greater than 255 results in negative PSNR.

NCC
C.
Normalized cross correlation (NCC) has been commonly used as a metric to evaluate the degree of similarity (or dissimilarity)
between two compared images. The main advantage of the normalized cross correlation over the cross correlation is that it is less
sensitive to linear changes in the amplitude of illumination in the two compared images.
Furthermore, the NCC is confined in the range between –1 and 1 to evaluate the performance the Normalized Cross-
Correlation (NCC) which is given by the following equation
 
 
1 1
2
1 1
N M
ij ij
i j
N M
ij
i j
x y
NCC
x
 
 




Comparison of Various Techniques
D.
Following table shows the comparison between various techniques studied in this paper:
Table 1:
Sr
.No.
Authors Year Features Advantages Disadvantages
1.
Neil F. Johnson
& Sushil
Jajodia
1998
Spatial Domain Technique Uses
LSB of pixel
Simple to implement
100 % chances of
insertion.
Not immune to noise and compression
technique Not Secure
3.
M. Chaumont et
al.,
2007
hides the color information in a
compress gray-level image
followed by quantization
less prone to attacks,
high compression
ratio
Not robust against rotation, cropping and
translation.
4.
Yang, Weng,
Wang
2008 Hides the data on edge area More secure Calculating edges are very complex.
5.
Adnan Abdul-
Aziz Gutub
2010
Use two least significant bits of
one channel to indicate existence
of data in the other two channels.
Take advantage of
24 bits
Computationally Complex
6.
Yadav et.al 2010 Parity of pixel bits are used for
message insertion & retrieval
Easy to implement
Not immune to noise & compression
7.
Parvinder at.al 2010
6th
, 7th
bit are used for message
insertion
Chances of insertion
are 50%
Not optimal chances of insertion, If intruder
change LSB, secret data may be affected,
Not immune to compression and noise.
8.
Yadav et.al 2011 6th , 7th & 8th bit are used for
message insertion
Chances are message
insertion are 85.49%
Hiding capacity is less
V. CONCLUSION
In this paper we have reviewed some steganographic techniques, different parameters and different methods for analyzing of
original image and stego image. We have reviewed techniques like LSB, parity checker method, pixel value indicator, 6th, 7th
bit method, 6th, 7th & 8th bit method, etc. with their advantages and disadvantages. In future we will try to develop a new image
steganography technique which will cover the limitations of these techniques.
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