A RSA- DWT Based Visual Cryptographic Steganogrphy Technique by Mohit Goel

ISSN: 2277 – 9043

International Journal of Advanced Research in Computer Science and Electronics Engineering

Volume 1, Issue 2, April 2012

95 All Rights Reserved © 2012 IJARCSEE

Abstract— With the development of science, digital media

can be transmitted conveniently over the internet. The security

of the data is essential issue for the internet. The security of

information can be achieved by cryptography and

steganography. Cryptography scrambles the data to hides the

contents of message. Steganography hides the existence of

message by embedding data in some other digital media like

image or audio files. The paper proposes a security method

which uses both encryption and data hiding. In proposed system

data is firstly encrypted using RSA encryption algorithm and

then embedded in an image using Haar-DWT based

steganographic method. The experimental result shows that

proposed system has better PSNR value and high capacity in

comparison to other techniques like LSB and LSB-DCT

steganography.

Index Terms— data hiding, discrete wavelet transform, RSA

encryption, steganography.

I. INTRODUCTION

In this information era, either a public network or private

network, one requires a tool that can allow communicating

over these channels and as well providing the security and

robustness of the hiding data. Encryption and steganography

are the preferred techniques for protecting the transmitted

data. In Cryptography, the data is encrypted so that it cannot

be understood by anyone else. The encrypted data is

unreadable but is not hidden from the eavesdroppers. Though

the purpose of cryptography is to protect the data (or

information) from unwanted attackers, it does not ensure

covertness on the channel. The commonly used encryption

schemes include DES (Data Encryption Standard) [1], AES

(Advanced Encryption Standard) [2] and RSA [3]. DES, an

encryption standard that was used by many national

governments, successfully withstood attacks for many years.

However, E. Biham and A. Shamir mention a cryptanalytic

attack that can break DES in only a few minutes. Another

example of a broken encryption algorithm is WEP. WEP was

designed to provide confidentiality to users on wireless

networks. [3] Illustrates how WEP can be broken within

Manuscript received April 15, 2012..

Mohit Kumar Goel, Electronics and Elecrical Communication

Department, PEC University of Technology, Chandigarh, India ,

Dr. Neelu Jain, Electronics and Elecrical Communication Department,

PEC University of Technology, Chandigarh, India,

hours. DES and WEP are examples of two encryption

algorithms that were thought to be secure at the time of their

design, but were broken in the future when attackers had

more powerful computational resources. However,

encryption clearly marks a message as containing

“interesting” information, and the encrypted message

becomes subject to attack. So, in many cases it is desirable to

send information without being notice by anyone that

information has been sent. The Steganography solves this

problem by embedding data in the cover object so that it is

hard to detect. The word steganography in Greek means

“covered writing” (Greek words “stegos” meaning “cover”

and “grafia” meaning “writing”). Steganography differs from

cryptography in the sense that where cryptography focuses

on concealing the contents of a message, steganography

focuses on concealing the existence of a message. Image

steganography schemes can be divided into two categories:

Spatial Domain and Frequency Domain.

A. Spatial domain steganography

In spatial domain steganography data is embedded directly

in image pixels [4].Least Significant Bit (LSB) is the first

most widely used spatial domain steganography technique. It

hides the message in the LSB of the image pixels [5]. But the

problem with this technique is that if the image is compressed

then the embedded data may be lost. LSB has been improved

by using a Pseudo Random Number Generator (PRNG) and a

secret key in order to have private access to the embedded

information [6]. Another recent improvement based on

random distribution of the message was introduced by M.

Bani Younes and A. Jantan [7]. In this method they utilize an

encryption key to hide information about horizontal and

vertical blocks where the secret message bits are randomly

concealed. Modulus arithmetic steganography proposed by

Sayuthi Jaafar and Azizah A Manaf has calculated last four

bits of each pixel by mod-16 operation. Then these bits are

replaced with data bits [8]. In this the amount of the data that

can be embedded is more but stego image has less PSNR

value than LSB and SSB-4 techniques.

B. Frequency domain steganography

In frequency domain, images are first transformed and

then the message is embedded in the image [9]. When the

data is embedded in frequency domain, the hidden data

resides in more robust areas, spread across the entire image,

and provides better resistance against statistical attacks.

There are many techniques used to transform image from

spatial domain to frequency domain. The most common

A RSA- DWT Based Visual Cryptographic

Steganogrphy Technique

Mohit Kumar Goel, Dr. Neelu Jain

ISSN: 2277 – 9043



96

frequency domain method usually used in image processing

is the 2D discrete cosine transform (DCT) [10][11] and 2D

discrete wavelet transform[12]. In DCT steganography the

image is divided into 8×8 blocks and DCT transformation on

each block is performed. The data bits are embedded in the

low frequency coefficients of DCT. SSB-4 & DCT

steganography proposed by Nedal M. S. Kafri and Hani Y

Suleiman uses DCT approach with SSB-4 technique [11].

The DWT steganography uses both image‟s spatial as well as

frequency characterstics. DWT divides the image in four sub

bands (LL, LH, HL and HH) and then data can be embedded

in coefficients of one of the selected sub band.

Steganography with cryptography can be combined so

that, even if an attacker does realize that a message is sent, he

would still have to decode it [13]. Piyush Marwaha and

Paresh Marwaha use DES encryption and LSB

steganography for data security [14]. In this paper we

propose a method which uses RSA encryption and DWT

steganography for data security.

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(),(),(1 2

1

0

1

0

m

i

n

j

jiKjiImn

MSE

Where MSE is the Mean Squared Error of Original image

(I) and stego image (K). Thereafter PSNR value is calculated

as follow:

)2(log.20log.10 10

2

10

MSE

MAX

MSE

MAXPSNR ii

Where, MAXi is the maximum pixel value of the image. In

other words MAXi = 2b − 1, where b is the bit depth of the

original image. The larger PSNR indicates the higher the

image quality i.e. there is only little difference between the

cover-image and the stego-image. On the other hand, a

smaller PSNR means there is huge distortion between the

cover-image and the stegoimage.

II. BACKGROUND OF CRYPTOGRPHY

In cryptography, the message is scrambled to make it

meaningless and unintelligible unless the decryption key is

available. It makes no attempt to disguise or hide the encoded

message. Basically, cryptography offers the ability of

transmitting information between persons in a way that

prevents a third party from reading it. Cryptography can also

provide authentication for verifying the identity of someone

or something. There are several ways of classifying

cryptographic algorithms. The three types of algorithms are:

1) Secret Key Cryptography: Uses a single key for both

encryption and decryption.

2) Public Key Cryptography: Uses one key for

encryption and another for decryption.

3) Hash Functions: Uses a mathematical transformation

to irreversibly “encrypt” information.

A. RSA encryption algorithm

RSA is a Public key cryptography named after its

inventors: Ronald Rivest, Adi Shamir and Leonard Adleman.

RSA can be used for encryption as well as for authentication

[3]. An example of Alice and Bob, who want to use

asymmetric RSA algorithm for secure communication is

shown in fig. 1. For encryption purpose, Alice would encrypt

the message using Bob‟s Public key and send the cipher text

to Bob. Upon receiving the cipher text, Bob, who is owner of

corresponding private key, can then decrypt the message with

his private key. For authentication purposes, Alice would

encrypt (or sign) the message using her own private key.

Other people such as Bob can verify the authenticity of the

message by using Alice‟s Public key, which is the only key

that matches the signing private key.

Fig. 1 RSA Encryption

The steps for RSA algorithm are:

1) Select two prime numbers r, s.

2) Calculate n= r × s and φ(n)= (r-1)(s-1)

3) Select integer „e‟ such that e is relatively prime to

φ(n).

gcd (φ (n),e)=1; 1<e < φ(n)

4) Calculate d such that d × e=1mod(φ (n))

5) Now Public key (PU) for encryption is {e, n} and

Private Key (PR) for decryption is {d, n}.

6) At sender side, message (M) is converted into cipher

text (C) as follows:

C= Me mod n (3)

7) At receiver side, cipher text is converted back to

original message as follows:

M= Cd mod n (4)

III. HAAR- DWT TRANSFORM

Wavelets are special functions which (in a form

analogous to sins and cosines in Fourier analysis) are used

as basal functions for representing signals. In addition to

being an efficient, highly intuitive framework for the

ISSN: 2277 – 9043




representation and storage of multiresolution images, the

DWT provides powerful insight into an image‟s spatial and

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

operation until all the columns are processed. Finally 4

sub-bands denoted as LL, HL, LH, and HH respectively are

obtained. The LL sub-band is the low frequency portion and

hence looks very similar to the original image.

Fig. 3 The vertical operation

The first-order 2-D Haar-DWT applied on the image

“woman” is illustrated in Fig 4.

Fig. 4 Haar DWT Operation

IV. PROPOSED METHOD

The challenge in this work was to find a way to

camouflage a secret message in an image without perceptible

degrading the image quality and to provide better resistance

against steganalysis process. The data is first converted into

cipher text using RSA encryption and the hided into lower

frequency component of image using Haar-DWT

steganography.

Fig. 5 Proposed Method

A. Embedding algorithm

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).

3) Apply mod2 operation on coefficients (Pi) of selected

sub band (LH) and modify it to hide data (mi) in

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-

IDWT transform.

5) Send the stego image to receiver.

B. Extraction algorithm

Steps for extraction algorithm are given as follows:

Input: An M×N size Stego image.

Output: Secret message.

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98

1) Perform Haar-DWT transform on stego image to

decompose it into four sub bands (LL, LH, HL and

HH).

2) Apply mod2 operation on coefficients (Pi) of selected

sub band (LH) to extract data (mi) in following way:

Qi = mod2 (Pi)

Message bit mi = Qi

3) Concatenate the message bits to obtain cipher message.

4) Decrypt the cipher message using RSA decryption keys

and display it on screen.

V. EXPERIMENTAL RESULTS

Since the visual detection of stego images is depending on

the nature of the image [15] so, varieties of image categories

are utilized in the experiments. The experimental image data

set consists of 100 JPEG images, which were taken by digital

camera. We focused on short messages with length of 3000

bits because they are the most challenging to detect [15].

(a) Original animal.jpg (b) Stego animal.jpg

(c) Original human.jpg (d) Stego human.jpg

(e) Original building.jpg (f) Stego building.jpg

(g) Original flower.jpg (h) Stego flower.jpg

Fig. 6 Original Images and Stego Images using DCT steganography

Comparative analysis of LSB, LSB-DCT, and proposed

method has been done on the basis of Peak signal to noise

ratio (PSNR). The comparative analysis of PSNR value of

different steanography technique, is given in table 1, shows

that proposed method of steganography has better image

quality of stego image than other techniques.

Table 1. Comparative analysis of PSNR values of different

steganography techniques

Image PSNR Value

LSB LSB-DCT RSA & DWT

animal.jpg 52.62 54.66 55.87

human.jpg 53.31 55.24 57.36

building.jpg 53.12 54.46 56.52

flower.jpg 52.78 54.86 56.35

VI. CONCLUSION

In this paper we used a mixed approach cryptography and

steganography is used for data security. By using RSA

encryption, ASCII codes corresponding to characters of plain

text are converted into 16 bits encrypted codes. Hence it

becomes difficult to get original text without knowing

decryption keys. Then cipher data is hided into cover image.

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

the improvement and further development in this technique.

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A RSA- DWT Based Visual Cryptographic Steganogrphy Technique by Mohit Goel

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