10.chapter 1 Jain
10.chapter 1 Jain
10.chapter 1 Jain
CHAPTER 1
Introduction
Modern development in technologies have created threats to secure data
transmission in digital communication and networking. Cryptography and Steganography
are the two techniques which supports in attaining security goals. Cryptography involves
scrambling of data by using different transformations whereas Steganography mainly
deals with concealing the secret data in a cover media in such a way that presence cannot
be identified.
1.1 Steganography
Steganography is the art of hiding information in a cover media for secret and
secure communication. The obtained image which carries the secret data or information
is termed as stego image. The existence of secret information in the stego image cannot
be detectable to any un intended person. The important qualities of any steganographic
system are (i)high capacity payload embedding (ii) better PSNR (iii) robustness to some
distortion caused by un authorized persons or noises in the communication systems. The
requirements of Steganographic systems are embedding module and retrieval module.
The embedding module at the sender’s end functions in embedding the secret data or
payload to the cover image to obtain stego image using any one of Steganographic
techniques. The retrieval module at the receiver’s end applies inverse Steganographic
algorithm to extract the hidden secret information from the stego image. The application
of steganography can be utilized to protect intellectual property rights i.e., to enforce copy
right and also to convey information to only those entities who are authorized.
Some of the other application of steganography are (i) secret and secure
communications in military (ii) secure Ecommerce (iii) protecting intellectual property (iv)
Authentication or verification (v) Safeguarding bank accounts/electronic transfers (vi) to
hide details of patients.
Providing security is the crucial problem in system and network technology
related application. The available security methods which could be easily implemented
lack to satisfy the critical requirement of emerging networks. There is a huge gap
between developers of security and developers of networks. The other related problems
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are platform oriented. Open System interface (OSI ) architecture offers modularity,
flexibility ,ease-of-use and standardization of protocols. Whenever network security is
concerned it is not only with respect to end to end communication but also providing
security of data on the communication channel which is vulnerable to attacks. Intruders
activity on the communication channel will be normally to extract the decrypted message
from the cipher and reinsert it onto the channel.
Due to growth in the internet and new networking technology the world is more
interconnected than before. This has resulted in the availability of large amount of data
regarding personal, commercial, military and government related information on the
network infrastructure. The analysis of network security is done based on the following
1. History of security in networks
2. Internet architecture and vulnerable security aspects of the Internet
3. Types of internet attacks and security methods
4. Security for networks with internet access
5. Current development in network security hardware and software
Based on this research, the future of network security is forecasted
1.1.1 Types of Steganography
The different types of steganography based on cover medium is as shown in fig.1.1
STEGANOGRAPHY
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Application of DCT divides the image into blocks 8x8 pixels. 2 D application of
the divided blocks results in 64 DCT coefficients. Depending of the size of the input
image these coefficients are formed into matrix. Thus even when there is a modification
on a single DCT coefficient will have a direct impact on the entire block of 64 pixels.
Pseudorandom block is embedded with i-th message bit and then embedding process is
started. Location of two DCT coefficients should be known to both sender and the
receiver before the communication starts. These chosen coefficients should correspond to
the middle frequencies to avoid losses while compression in JPEG. After the data being
embedded inverse DCT if applied which results in stego image. While retrieval every
clock is compared with respect to coefficients in every block and information is restored.
1.2.5 Discrete Wavelet Transform
To convert spatial domain to frequency domain Discrete Wavelet Transform can
be used.
On pixel by pixel basis DWT separates high frequency and low frequency components. It
can analyze different frequencies by different resolutions and hence is known as a multi-
resolution technique. In this, an image is divided into four sub-bands and the sub-band
with the lowest frequency undergoes another level of decomposition. The four sub-bands
obtained are:
LL (Horizontally and vertically low pass)
LH (Horizontally low pass and vertically high pass)
HL (Horizontally high pass and vertically low pass)
HH (Horizontally and vertically low pass)
These are also called as Approximation, Horizontal, Vertical and Diagonal Coefficients
respectively. Image steganography technique using DWT one can use any one of high
frequency sub-bands to embed secret data. Very existence of secret data is invisible and
hence goal of steganography is attained.
1.3 Comparison between DCT and DWT
In image steganography both the transformation techniques like DCT and DWT
can be used. DCT operates on blocks of independent pixels. DCT, when used at high
compression rates might result in annoying blocking artifact. This drawback of DCT is
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eliminated using DWT. DWT applies on entire image. Larger amount of secret data can
be hidden in DWT than in DCT. Each block carries single secret data bit whereas three
high frequency sub-bands can be used to embed the data in DWT technique.
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Security
Goals
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1.7 Steganalysis
The method or attack used to extract the information from stego images is called
as Steganalysis. There are three types of Steganalysis, namely Visual attacks, statistical
attacks and structural attacks.
(a) Visual attacks: using naked eye or with the help of the computer if one can identify
the presence of hidden data then this type of attack is termed as visual attack.. Further
analysis is done to separate the image into bit planes.
(b) Statistical attacks: In Statistical attack mathematical tools are used to identify the
smallest changes that are resulted while applying Steganographic algorithm. These types
of attacks are highly powerful and successful. There are two types of attacks one is called
passive attack and the other is called active attack. In passive attack only presence of the
secret data is identified whereas in active attacks the length, location and existence of
secret key is also been revealed
(c) Structural attacks: Usually after the application of Steganographic technique the
format of the data file gets altered. Analysis done on this type of structural based concept
is termed as structural attacks.
1.8 Motivation
In the past, there have been many developments in the secure communication
problem. Modifying existing methods to efficient and effective communication is done
using steganography where the messages such as images, videos, sound files, text and
other computer files can be hidden inside or other digital objects which remains invisible
to an ordinary observer. A detailed study and analysis and improvement over the existing
technology are the central concept of research.
1.9 Objective
The objective of this thesis is to design and develop an efficient Steganographic
algorithm against Steganalysis for Secure Communication.
Study different image processing algorithm for secure communication.
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1.10 Methodology
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This chapter gives an algorithm which uses error replacement method like
minimum error replacement method and Advanced Error Replacement Method to attain
good PSNR. To add randomness to the embedding procedure which increases security,
Variable Embedding can be employed in which a suitable embedding ratio is chosen and
according to that the message bits are embedded into the image pixels. The increase in the
payload decrease PSNR value, which indicates image degradation amount. To improve
PSNR Minimum Error Replacement [MER] method is used. In this method the next
higher bit than the last embedded bit is toggle to decrease the pixel error.
Chapter 4 describes Stego and crypto way of embedding the data, especially in
Multiresolution analysis. This chapter has explained the use of Multiresolution analysis
on wavelets and Curvelets. The experimental analysis explained in this chapter has
proved that Curvelets is the best Multiresolution transformation available. Even if the
image carrying embedded data i.e., Stego image undergoes a reverse operation, data
cannot be extracted if the receiver is unaware of the exact coordinates of the geometric
shape. Hence retrieving secret image for an attacker becomes a hard task. Experimental
results are verified for both the properties of Cryptography and Steganography.
Chapter 5 explains frequency domain technique used to develop an algorithm for
Stganography. Skin tone algorithm is developed and explained for four different
embedding procedures. Another feature used in data hiding i.e. cropping of image. The
cropped image is used in different steps of data hiding. This cropping feature increases
the security than the use of whole image. So, this cropped region used as the key at
decoding side. This shows that the mechanism of hiding the information in skin tone
region of images gives higher security.
Chapter 6 gives overall conclusion with respect to algorithm developed. It also explains
the way in which security related parameters could be improved by employing few other
Steganographic techniques.
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hiding capacity is improved and secrecy of the embedded data bits can be provided. It is
also seen that the stego image formed is of good quality.
A new way of hiding the data in image through geometrical figures [9] which
takes the advantages of both cryptography and Steganography is proposed. Here origin
and radius of the circle acts as a key in selecting the pixels. Radius and origin depends
upon the amount of data that are being hidden, selecting pixels can’t be identified since
they look as other common pixels even after they are modified with data.
Multiple Edge Detection and Variable Embedding increases the maximum data
hiding capacity and the minimum error Replacement [4] method compensates for the
PSNR reduction caused by them.
The image is compressed by 3 levels by using discrete wavelet transform and the
compressed image [7] is recovered by using inverse discrete wavelet transform. The
original image is recovered. The peak signal-to-noise ratio is 55.62 and mean square error
is 0.178. Number of coefficients recovered is 99.94 %. Standard deviation is 2.537.
Median absolute deviation is 0.943. Mean absolute deviation is 1.642.
An algorithm [3] for embedding the data by considering the decimal value of the
data is developed. The data to be embedded is first converted into decimal values, and
then these decimal values are used to embed the data. Here instead of directly replacing
the LSB with the data bits, the magnitude of the input data to just compliment certain
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LSB bits are being used. With this method the security increases significantly with little
Instead of embedding secret image in the whole cover image, it is been embedded
only in skin pixels of cover image. The proposed method [8] uses HSV (Hue, Saturation
and Value) color space for skin detection & Haar DWT (Discrete Wavelet Transform) as
frequency transform method. The proposed method uses skin tone detection for finding
skin portion of image and within this skin portion secret data embedding is done using
DWT domain. Four cases of embedding are considered. It is observed that hiding of
secret data in only the cropped skin portion enhances the security.
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