Data security by RSA DWT Steganography

1. ISSN: 2277 – 9043
International Journal of Advanced Research in Computer Science and Electronics Engineering
Volume 1, Issue 2, April 2012
A RSA- DWT Based Visual Cryptographic
Steganogrphy Technique
Mohit Kumar Goel, Dr. Neelu Jain
 hours. DES and WEP are examples of two encryption
Abstract— With the development of science, digital media algorithms that were thought to be secure at the time of their
can be transmitted conveniently over the internet. The security design, but were broken in the future when attackers had
of the data is essential issue for the internet. The security of more powerful computational resources. However,
information can be achieved by cryptography and
steganography. Cryptography scrambles the data to hides the
encryption clearly marks a message as containing
contents of message. Steganography hides the existence of “interesting” information, and the encrypted message
message by embedding data in some other digital media like becomes subject to attack. So, in many cases it is desirable to
image or audio files. The paper proposes a security method send information without being notice by anyone that
which uses both encryption and data hiding. In proposed system information has been sent. The Steganography solves this
data is firstly encrypted using RSA encryption algorithm and problem by embedding data in the cover object so that it is
then embedded in an image using Haar-DWT based
steganographic method. The experimental result shows that
hard to detect. The word steganography in Greek means
proposed system has better PSNR value and high capacity in “covered writing” (Greek words “stegos” meaning “cover”
comparison to other techniques like LSB and LSB-DCT and “grafia” meaning “writing”). Steganography differs from
steganography. cryptography in the sense that where cryptography focuses
on concealing the contents of a message, steganography
Index Terms— data hiding, discrete wavelet transform, RSA focuses on concealing the existence of a message. Image
encryption, steganography. steganography schemes can be divided into two categories:
Spatial Domain and Frequency Domain.
I. INTRODUCTION A. Spatial domain steganography
In this information era, either a public network or private In spatial domain steganography data is embedded directly
network, one requires a tool that can allow communicating in image pixels [4].Least Significant Bit (LSB) is the first
over these channels and as well providing the security and most widely used spatial domain steganography technique. It
robustness of the hiding data. Encryption and steganography hides the message in the LSB of the image pixels [5]. But the
are the preferred techniques for protecting the transmitted problem with this technique is that if the image is compressed
data. In Cryptography, the data is encrypted so that it cannot then the embedded data may be lost. LSB has been improved
be understood by anyone else. The encrypted data is by using a Pseudo Random Number Generator (PRNG) and a
unreadable but is not hidden from the eavesdroppers. Though secret key in order to have private access to the embedded
the purpose of cryptography is to protect the data (or information [6]. Another recent improvement based on
information) from unwanted attackers, it does not ensure random distribution of the message was introduced by M.
covertness on the channel. The commonly used encryption Bani Younes and A. Jantan [7]. In this method they utilize an
schemes include DES (Data Encryption Standard) [1], AES encryption key to hide information about horizontal and
(Advanced Encryption Standard) [2] and RSA [3]. DES, an vertical blocks where the secret message bits are randomly
encryption standard that was used by many national concealed. Modulus arithmetic steganography proposed by
governments, successfully withstood attacks for many years. Sayuthi Jaafar and Azizah A Manaf has calculated last four
However, E. Biham and A. Shamir mention a cryptanalytic bits of each pixel by mod-16 operation. Then these bits are
attack that can break DES in only a few minutes. Another replaced with data bits [8]. In this the amount of the data that
example of a broken encryption algorithm is WEP. WEP was can be embedded is more but stego image has less PSNR
designed to provide confidentiality to users on wireless value than LSB and SSB-4 techniques.
networks. [3] Illustrates how WEP can be broken within B. Frequency domain steganography
In frequency domain, images are first transformed and
Manuscript received April 15, 2012.. then the message is embedded in the image [9]. When the
Mohit Kumar Goel, Electronics and Elecrical Communication data is embedded in frequency domain, the hidden data
Department, PEC University of Technology, Chandigarh, India , resides in more robust areas, spread across the entire image,
and provides better resistance against statistical attacks.
Dr. Neelu Jain, Electronics and Elecrical Communication Department, There are many techniques used to transform image from
PEC University of Technology, Chandigarh, India, spatial domain to frequency domain. The most common
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All Rights Reserved © 2012 IJARCSEE

2. ISSN: 2277 – 9043
International Journal of Advanced Research in Computer Science and Electronics Engineering
Volume 1, Issue 2, April 2012
frequency domain method usually used in image processing 2) Public Key Cryptography: Uses one key for
is the 2D discrete cosine transform (DCT) [10][11] and 2D encryption and another for decryption.
discrete wavelet transform[12]. In DCT steganography the 3) Hash Functions: Uses a mathematical transformation
image is divided into 8×8 blocks and DCT transformation on to irreversibly “encrypt” information.
each block is performed. The data bits are embedded in the A. RSA encryption algorithm
low frequency coefficients of DCT. SSB-4 & DCT RSA is a Public key cryptography named after its
steganography proposed by Nedal M. S. Kafri and Hani Y inventors: Ronald Rivest, Adi Shamir and Leonard Adleman.
Suleiman uses DCT approach with SSB-4 technique [11]. RSA can be used for encryption as well as for authentication
The DWT steganography uses both image‟s spatial as well as [3]. An example of Alice and Bob, who want to use
frequency characterstics. DWT divides the image in four sub asymmetric RSA algorithm for secure communication is
bands (LL, LH, HL and HH) and then data can be embedded shown in fig. 1. For encryption purpose, Alice would encrypt
in coefficients of one of the selected sub band. the message using Bob‟s Public key and send the cipher text
Steganography with cryptography can be combined so to Bob. Upon receiving the cipher text, Bob, who is owner of
that, even if an attacker does realize that a message is sent, he corresponding private key, can then decrypt the message with
would still have to decode it [13]. Piyush Marwaha and his private key. For authentication purposes, Alice would
Paresh Marwaha use DES encryption and LSB encrypt (or sign) the message using her own private key.
steganography for data security [14]. In this paper we Other people such as Bob can verify the authenticity of the
propose a method which uses RSA encryption and DWT message by using Alice‟s Public key, which is the only key
steganography for data security. that matches the signing private key.
Security and robustness are the main aspects affecting
steganography and its usefulness. Security relates to the
ability of an eavesdropper to figure the hidden information
easily. Robustness is concerned about the resist possibility of
modifying or destroying the unseen data.
C. PSNR (Peak Signal to Noise Ratio)
PSNR computes the peak signal to noise ratio, in decibels,
between two images. This ratio is used as quality
measurement between two images. To calculate PSNR; first
MSE is calculated as follows:
1 m1 n 1
MSE   I (i, j)  K (i, j)
mn i 0 j 0
2
(1)
Where MSE is the Mean Squared Error of Original image
(I) and stego image (K). Thereafter PSNR value is calculated
as follow:
 MAX i
2
  MAX i 
PSNR  10. log 10 
 MSE   20. log 10 
  ( 2) Fig. 1 RSA Encryption
   MSE 
The steps for RSA algorithm are:
Where, MAXi is the maximum pixel value of the image. In
other words MAXi = 2b − 1, where b is the bit depth of the 1) Select two prime numbers r, s.
original image. The larger PSNR indicates the higher the 2) Calculate n= r × s and φ(n)= (r-1)(s-1)
image quality i.e. there is only little difference between the 3) Select integer „e‟ such that e is relatively prime to
cover-image and the stego-image. On the other hand, a φ(n).
smaller PSNR means there is huge distortion between the gcd (φ (n),e)=1; 1<e < φ(n)
cover-image and the stegoimage. 4) Calculate d such that d × e=1mod(φ (n))
5) Now Public key (PU) for encryption is {e, n} and
II. BACKGROUND OF CRYPTOGRPHY Private Key (PR) for decryption is {d, n}.
6) At sender side, message (M) is converted into cipher
In cryptography, the message is scrambled to make it
text (C) as follows:
meaningless and unintelligible unless the decryption key is
C= Me mod n (3)
available. It makes no attempt to disguise or hide the encoded
7) At receiver side, cipher text is converted back to
message. Basically, cryptography offers the ability of
original message as follows:
transmitting information between persons in a way that
M= Cd mod n (4)
prevents a third party from reading it. Cryptography can also
provide authentication for verifying the identity of someone III. HAAR- DWT TRANSFORM
or something. There are several ways of classifying Wavelets are special functions which (in a form
cryptographic algorithms. The three types of algorithms are: analogous to sins and cosines in Fourier analysis) are used
1) Secret Key Cryptography: Uses a single key for both as basal functions for representing signals. In addition to
encryption and decryption. being an efficient, highly intuitive framework for the
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3. ISSN: 2277 – 9043
International Journal of Advanced Research in Computer Science and Electronics Engineering
Volume 1, Issue 2, April 2012
representation and storage of multiresolution images, the frequency component of image using Haar-DWT
DWT provides powerful insight into an image‟s spatial and steganography.
frequency characteristics. The fourier transform and DCT,
on other hand, reveal only image‟s frequency attributes.
The discrete wavelet transform (DWT) used in this paper is
Haar-DWT, the simplest DWT. A 2-dimensional
Haar-DWT consists of two operations which are described
as follows:
Step 1: Scan the pixels from left to right in horizontal
direction and perform the addition and subtraction
operations on neighboring pixels. Store the sum on the left
and the difference on the right as shown in Figure 2. Repeat
this operation until all the rows are processed. The pixel
sums represent the low frequency part (denoted as symbol
L) while the pixel differences represent the high frequency
part of the original image (denoted as symbol H).
Fig. 2 The horizontal operation on the first row
Step 2: Scan the pixels from top to bottom in vertical
direction and perform the addition and subtraction operations
on neighboring pixels. Then store the sum on the top and the
difference on the bottom as illustrated in Figure 3. Repeat this
Fig. 5 Proposed Method
operation until all the columns are processed. Finally 4
sub-bands denoted as LL, HL, LH, and HH respectively are
A. Embedding algorithm
obtained. The LL sub-band is the low frequency portion and
hence looks very similar to the original image. Steps of embedding algorithm are given as follow:
Input: An M×N size cover image and data to be concealed.
Output: Stego image.
1) Encrypt the plain text using RSA encryption key.
2) Perform Haar-DWT transform on cover image to
decompose it into four sub bands (LL, LH, HL and
HH).
Fig. 3 The vertical operation 3) Apply mod2 operation on coefficients (Pi) of selected
The first-order 2-D Haar-DWT applied on the image sub band (LH) and modify it to hide data (mi) in
“woman” is illustrated in Fig 4. following way:
Qi = mod2 (Pi)
a) If Qi is 0 i.e. Pi is even then
Modified coefficients MPi = Pi+ mi or
b) If Qi is 1 i.e. Pi is odd then
Modified coefficients MPi = (Pi-1) + mi
4) Four sub bands including modified sub band are
combined to generate stego image using Haar-
Fig. 4 Haar DWT Operation IDWT transform.
5) Send the stego image to receiver.
IV. PROPOSED METHOD
The challenge in this work was to find a way to B. Extraction algorithm
camouflage a secret message in an image without perceptible Steps for extraction algorithm are given as follows:
degrading the image quality and to provide better resistance
against steganalysis process. The data is first converted into Input: An M×N size Stego image.
cipher text using RSA encryption and the hided into lower Output: Secret message.
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All Rights Reserved © 2012 IJARCSEE

4. ISSN: 2277 – 9043
International Journal of Advanced Research in Computer Science and Electronics Engineering
Volume 1, Issue 2, April 2012
1) Perform Haar-DWT transform on stego image to Table 1. Comparative analysis of PSNR values of different
decompose it into four sub bands (LL, LH, HL and steganography techniques
HH). PSNR Value
Image
2) Apply mod2 operation on coefficients (Pi) of selected LSB LSB-DCT RSA & DWT
sub band (LH) to extract data (mi) in following way: animal.jpg 52.62 54.66 55.87
Qi = mod2 (Pi)
human.jpg 53.31 55.24 57.36
Message bit mi = Qi
3) Concatenate the message bits to obtain cipher message. building.jpg 53.12 54.46 56.52
4) Decrypt the cipher message using RSA decryption keys flower.jpg 52.78 54.86 56.35
and display it on screen.
VI. CONCLUSION
V. EXPERIMENTAL RESULTS
In this paper we used a mixed approach cryptography and
Since the visual detection of stego images is depending on steganography is used for data security. By using RSA
the nature of the image [15] so, varieties of image categories encryption, ASCII codes corresponding to characters of plain
are utilized in the experiments. The experimental image data text are converted into 16 bits encrypted codes. Hence it
set consists of 100 JPEG images, which were taken by digital becomes difficult to get original text without knowing
camera. We focused on short messages with length of 3000 decryption keys. Then cipher data is hided into cover image.
bits because they are the most challenging to detect [15]. Average PSNR value of 56 is obtained for 100 images using
proposed method. The obtained experimental results indicate
that, the proposed method is a good and acceptable scheme
for data security. Furthermore, by embedding information in
the least significant bits of the DWT domain, the hidden
message resides in more robust areas, spread across the entire
stego image, and provides better resistance against statistical
attacks than other techniques. The future work may focus on
(a) Original animal.jpg (b) Stego animal.jpg the improvement and further development in this technique.
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International Journal of Advanced Research in Computer Science and Electronics Engineering
Volume 1, Issue 2, April 2012
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