This paper gives the idea of recent developments in the field of image security and improvements in image security. Images are used in many applications and to provide image security using image encryption and authentication. Image encryption techniques scramble the pixels of the image and decrease the correlation among the pixels, such that the encrypted image cannot be accessed by unauthorized user.

1. International Journal of Electrical & Electronics Engineering 14 www.ijeee-apm.com
IJEEE, Vol. 1, Issue 1 (Jan-Feb 2014) e-ISSN: 1694-2310 | p-ISSN: 1694-2426
Design of Selective Encryption Scheme
Using Matlab
Abhishek Thakur1
, Rajesh Kumar2
, Amandeep Bath3
, Jitender Sharma4
1,2,3,4
Electronics & Communication Department, IGCE, Punjab, India
1
abhithakur25@gmail.com, 2
errajeshkumar2002@gmail.com
3
amandeep_batth@rediffmail.com, 4
er_jitender2007@yahoo.co.in
Abstract- This paper gives the idea of recent developments
in the field of image security and improvements in image
security. Images are used in many applications and to provide
image security using image encryption and authentication.
Image encryption techniques scramble the pixels of the image
and decrease the correlation among the pixels, such that the
encrypted image cannot be accessed by unauthorized user.
This study proposes a method for encrypting the sender’s
messages using new algorithm called Chaotic encryption
method. This key will be used for encrypting and decrypting
the messages which are transmitted between two sides.
Chaotic encryption technique is the new way of cryptography.
Emphasizing the image security, this paper is to design the
enhanced secure algorithm which uses Chaotic encryption
method to ensure improved security and reliability.
Keywords— Cryptography, Cryptography key, RGB image,
LSB, image key.
II. INTRODUCTION
Across the internet information exchanges and the
storage of data in open networks have created an environment
in which illegal users can obtain the important information.
Encryption algorithms have been used to provide a kind of
randomness such that any unauthorized user cannot obtain the
secure data. Only the authorized user having the key can
obtain the original data. Images are used in many applications
such as medical imaging system, military image databases,
cable TV, confidential video conferencing, online personal
photograph album, etc. Hence, reliable, fast and robust
security techniques are required to store and transmit digital
images. In open environments, there are several security
problems associated with the processing and transmission of
digital images. Therefore it is necessary to affirm the integrity
and confidentiality of the digital image being transmitted. The
various techniques used in the existing image encryption
techniques can be classified into three major categories:
transposition techniques (position permutation), substitution
techniques (value transformation) and the combination i.e.
transposition-substitution technique [1]. The position
permutation techniques shuffle the pixel position within the
image itself and usually have low security because histogram
of the shuffled image remains same. If we talk about the value
transformation techniques, they modify pixel value of the
original image and have the potential of low computational
complexity and low hardware cost. Finally, the combination
performs both position permutation and value transformation
and has the potential of high security. Another technique for
securing digital images is based on the use of chaotic
functions [2].
III. TECHNIQUES USED
In recent years, a number of different image encryption
schemes have been proposed based on chaotic maps [3-12], in
order to overcome image encryption problems.
A. Cryptography
The cryptography has been proposed to ensure the
confidentiality and authenticity of the message. The
encryption key must be long. Yet, it is difficult to remember it
and even storing the key in a database or in a file may be
insecure. In addition the protection of the confidentiality of
encryption keys is one of the important issues to be dealt
with. This issue can be efficiently solved through generating
the key before starting the process of encryption and
decryption, rather than storing it. Here we will use an image
to generate the key. The main objective of this study is to
increase security in communication by encrypting the
information using a key that is created through using an
image. Cryptography presents various methods for taking
legible, readable data, and transforming it into unreadable
data for the purpose of secure transmission, and then using a
key to transform it back into readable data when it reaches its
destination [8]. Cryptography is considered to be one of the
fundamental building blocks of computer security [4]. The
need of reliable and effective security mechanisms to protect
information systems is increasing due to the rising magnitude
of identity theft in our society. Although cryptography is a
powerful tool to achieve information security, the security of
cryptosystems relies on the fact that cryptographic keys are
secret and known only to the legitimate user [9]. In secure
communication, key generation phase has many challenges
and this problem can be solved if the sender and the receiver
share the key in any other form or if they generate the keys

2. www.ijeee-apm.com International Journal of Electrical & Electronics Engineering 15
readily during encryption and decryption separately, thus, the
concept of generating the key from an image came to the role.
B. Visual Cryptography
Visual Cryptography is a special encryption technique to
hide information in images in such a way that it can be
decrypted by the human vision if the correct key image is
used. In secret sharing mechanisms, the secret data is divided
into several shares (images) and distributed among
participants. Shares are stacked together to recover the data.
Visual cryptography (VC) attempts to recover a secret image
via the human visual system by stacking two or more
transparencies. In VC approach [1], the secret was partitioned
into n shadow images (shares), and each participant would
receive only one share. Once any k or more shares of a secret
are stacked together, the secret image will be visually
retrieved without the help of the computer. That is to say that
the secret image will be invisible if the number of stacked
shares is less than k. This is known as (k, n) threshold
mechanism. If the random looking shares are enveloped into
some meaningful images the interest of hackers can be
reduced.
C. Steganography
Hiding information by embedding secret data into an
innocuous medium is often referred to as steganography.
Steganography can be applied electronically by taking a
message (a binary file) and some sort of cover (often a sound
or image file) and combining both to obtain a “stego-object”.
The RS analysis is considered as one of the most famous
steganalysis algorithm which has the potential to detect the
hidden message by the statistic analysis of pixel values [1].
The process of RS steganalysis uses the regular and singular
groups as the considerations in order to estimate the
correlation of pixels [2]. The presence of robust correlation
has been witness in the adjacent pixels. But unfortunately
using traditional LSB replacing steganography [3], the system
enders the alteration in the proportion in singular and regular
groups which exposes the presence of the steganography.
Ultimately, it will not be so hard to decrypt the secret
message. Although there are extensive researches based on
combining these two approaches [4] [5] [6], but the results are
not so satisfactory with respect to RS analysis. Other
conventional methods of image security has witnessed the use
of digital watermarking extensively, which embeds another
image inside an image, and then using it as a secret image [7].
The use of steganography in combination visual cryptography
is a sturdy model and adds a lot of challenges to identifying
such hidden and encrypted data. The image is divided into a
number of blocks and each block is computed to produce hash
value. In the scheme, only the hash value is encrypted using
the chaotic logistic map and remaining block values are
computed using the transition function of linear memory
cellular automata. The method uses the concepts of linear
memory cellular automata (LMCA). The linear memory
cellular automata requires large number of computations and
one-by-one, each block of the image is computed using cells
of the cellular automata. If the method is applied over large
sized images, more number of blocks will be made and the
number of computations will be much more. In the scheme,
the number of blocks is not constant and can vary. Therefore,
if the blocks are of large size, then local transition function
will require much computations and if the block size is small
then more number of blocks will be there, which also requires
more computations to be performed. Hence, the method is
good butif we apply the scheme over small computation
devices (e.g. Micro devices that have less computational
power compared to a computer), the number of executions
will be a complex issue. The security provided by the scheme
is keen but the computation needs to be enhanced such that
the method can be adopted easily.
IV.SELECTIVE ENCRYPTION
The encryption process requires an encryption algorithm
and a key. The process of recovering plaintext from cipher
text is called decryption. The accepted view among
professional cryptographers (formalized in KIRKHOFF's law)
is that the encryption algorithm should be published, whereas
the key must be kept secret. Selective encryption scheme
generate the key before starting the process of encryption and
decryption, rather than storing it. In secure communication,
key generation phase has many challenges and this problem
can be solved if the sender and the receiver share the key in
any other form or if they generate the keys readily during
encryption and decryption separately.
Fig. 1: Encryption of an image.
From Fig. 1, it is clear that the receiver should decrypt the
information before it can decompress the image. This
approach has the main drawback that it is impossible to
access the smallest part of information without knowledge of
the key. For example, it would impossible to search through a
general database of fully encrypted images. A way to address
this issue is to use a technique called selective encryption; it is

3. International Journal of Electrical & Electronics Engineering 16 www.ijeee-apm.com
depicted in Fig. 2. The image is first compressed (if needed).
Afterwards the algorithm only encrypts part of the bitstream
with a well-proven ciphering technique; incidentally a
message (a watermark) can be added during this process. To
guarantee a full compatibility with any decoder, the bitstream
should only be altered at places where it does not compromise
the compliance to the original format. This principle is
sometimes referred to as format compliance. WEN et al. []
have recently described a general framework for format-
compliant encryption.
Fig. 2: Selective encryption mechanism.
A. Input Image
The simplest way to hide binary data on an image is to use
a lossless image format (such as a Bitmap) and replace the
least significant bits of each pixel in scan lines across the
image with the binary data. This is not secure as an attacker
can simply repeat the process to quickly recover the hidden
information. This technique, known here as “BlindHide”
because of the way it blindly hides information, is also not
good at hiding – the initial portion of the image is left
degraded while the rest remains untouched. The proposed
project work consist of mainly two algorithms which are (i)
Steganography using Genetic Algorithm (ii) Visual
Cryptography with Threshold. The application initiates with
Steganography module where the cover image will be
encrypted to generate Stego image. The stagographic image
generated in this module will act as an input for visual
cryptographic module.
Algorithm: Steganography
Input: Cover Image
Output: Stego Image
1) Read the cover image.
2) Find out the pixel values of cover image.
3) Read the secret data character wise.
4) Convert each character into its equivalent ASCII code.
5) ASCII code is converted into binary values.
6) Enter the secret key.
7) Secret data is converted into cipher data.
8) The stream of 8 bit(cipher data) are embedded into LSB
of each pixel of the cover image.
9) To apply Genetic Algorithm in the stego image the pixel
location should be modified.
Algorithm: Visual Cryptography
Input: Stego-Image
Output: Encrypted Shares
1) Read Stego-Image generated.
2) The stego image is breaked into three layers namely
split-1, split-2, split-3 these three files are containing the
hidden data and to get the hidden data these three files have to
be reconstructed perfectly.
3) The re-assembled picture and the extracted data will
be gained again. The proposed scheme is based on standard
visual cryptography as well as visual secret sharing. The
implementation of the algorithm yields in better result with
insignificant shares when stego images are normally with
light contrast. It can also be seen that the algorithm gives
much darker shares in gray output the proposed scheme is
based on standard visual cryptography as well as visual secret
sharing. The implementation of the algorithm yields in better
result with insignificant shares when stego images are
normally with light contrast. It can also be seen that the
algorithm gives much darker shares in gray output. This
algorithm gives better results in terms of image quality and
stegnalysis. good at hiding – the initial portion of the image is
left degraded while the rest remains untouched. The proposed
project work consist of mainly two algorithms which are (i)
Steganography using Genetic Algorithm (ii) Visual
Cryptography with Threshold. The application initiates with
Steganography module where the cover image will be
encrypted to generate Stego image. The stagographic image
generated in this module will act as an input for visual
cryptographic module. The original message is embedded into
the image by using LSB insertion method. The resultant
image is called as stego image shown in Figure 3. Then apply
genetic algorithm to modify the pixel location and detection
of message is complex.
Then apply visual cryptography scheme stego image is
splitted into two shares based on threshold. The shares of the
stego image is shown in Figure 4.
It is almost impossible for anyone who will attempt to
decrypt the encrypted data within that image to reveal if the
secret shares which they posses are set of all encrypted shares
or certain secret shares are missing.
V. PERFORMANCE ANALYSIS
The performance of the proposed system is experimented
by performing stegnalysis and conducting benchmarking test
for analysing parameters like Mean Squared Error (MSE) and
Peak Signal to Noise Ratio.
Cover image : rice.png
Size : 256*256
Mean Square Error (MSE) : 0.0678
Peak Signal-to-Noise Ratio (PSNR) : 59.8188db
After applying Genetic Algorithm the measured
performance is shown in below

4. www.ijeee-apm.com International Journal of Electrical & Electronics Engineering 17
Mean Square Error (MSE) : 0.794
Peak Signal-to-Noise Ratio (PSNR) : 39.4011db
After applying genetic algorithm all the pixel location are
altered. Due to the change the pixel location MSE and PSNR
values are increased.
From Figure 1 and 2, we can conclude that both the sender
and receiver before they start to communicate with each
other, they should use the same images database, image
channel (R, G or B), K value for the key array, and the
session type. This study implemented the key generation as 1
image/session. The session period can be an hour or one day.
For instance, hourly session uses one image for each hour and
the daily session uses one image for each day.
Phase 1: Database creation:
In this phase, we create a database of color RGB images
which would be used for generating the key for
encryption/decryption process. In case of using hourly
session, the database should contain 24 images; otherwise, it
should contain 7 images for the daily session. Both the sender
and the receiver should use the same database of images (24
or 7 images) as the names of the images should be the same in
both sides.
B. Key Generation:
In this section, we present the pseudo code for the key
generation algorithm and the algorithm steps as follows:
1. Get the value of K variable and the value of N from
binaries message step.
2. Select color image from the database according to the
session type and current date or time.
3. Retrievethe image and create array Img [x, y] as LSB of the
pixels for one channel (red, green or blue) where the
image has x*y dimension.
4. Create array Key [N, k] to represent the encryption key.
5. Loop i=0 to N-1 /* for each row in Key*/
6. Loop c=0 to k/2-1 step 2//fill array by two each7. Scan the
LSB Img[x,y] to find two neighbor values where the
absolute difference between them is one.
8. Key[i,c] = First LSB value.
9. Key[i,c+1] = Second LSB value.
10. End loop
11. End loop
C. Image Encryption
In this section, we present the pseudo code for the
encryption algorithm and the algorithm steps as follows:
1. Get the value of K variable.
2. Read a message to encrypt
3. Binaries the message and store the binary data in array
Data[N,N] where message bits <= N*N
4. Generate the key using key generation algorithm and create
Key [N, k].
5. Create array EncData [N, N] to store the encrypted data
6. c=0
7. Loop i=0 to N-1// for each row in Data /* the elements in
the Data array row i compare with two columns of Key
array start from c */
8. Loop j=0 to N-1// for each bit in the row i
9. If Data[i,j] = Key[j,c]
10. EncData[i,j]=0 // the value in the first column
11. Else
12. EncData[i,j]=1 // the value in the second column
13. End loop
14. c=c+2// go to next two columns of Key array.
15. if c >= K then c=0// return to the first two columns of Key
array
16. End loop
17. Convert the Enc. Data from binary data to text.
D. Decryption:
In this section, we present the pseudo code for the
decryption algorithm and the algorithm steps as follows:
1. Get the value of K variable.
2. Binaries the encrypted message and store the binary data
in array EncData[N,N]
3. Generate the key using key generation algorithm and
create Key [N, k].
4. Create Data[N, N] to store the original data
5. c=0
6. Loop i=0 to N-1 /* for each row in Data*//* the elements
in the Data array row i compare with two columns of
Key array start from c */
7. Loop j=0 to N-1 // for each bit in the row i
8. If Encdata[i,j]=0 then
VI.RESULTS
E. Results for image encryption and decryption
This figure shows the result of image encryption,
decryption and histogram of each image.
Input Image
Encrypted Image
Final Image
0
1000
2000
Histogram of input image
0 100 200
0
2000
Histogram of Encrypted image
0 100 200
0
1000
2000
Histogram of final Image
0 100 200
Fig. 3: Results for image encryption and decryption

5. International Journal of Electrical & Electronics Engineering 18 www.ijeee-apm.com
Image encryption and decryption algorithm is developed in
matlab. In the first step we take any image which we want to
encrypt and apply any key consist of number, words and
special character. When we apply this key to image its
visualization is hidden and its histogram is also change. When
we want to decrypt this image we need to enter same key. If
we provide wrong key then image will not decrypt.
Fig. 4: Results for image encryption and decryption
VII. CONCLUSIONS
Images play an important role in our lives. They are used in
many applications. Therefore it is necessary to affirm the
integrity and confidentiality of the digital image being
transmitted. Some image encryption and authentication
schemes are discussed in this paper and further improvements
are also suggested in the previous section. The chaos based
image cryptography is increasing and improving day by day.
The paper presents different chaos based image cryptographic
techniques proposed in the last decade. We discussed the
cryptanalysis of an image encryption scheme and conclude
that if the algorithm is not designed properly, it may be
possible that the image being protected will be insecure.
Therefore proper security mechanisms should be adopted to
secure the image. Each technique is unique and is suitable for
different applications. Everyday new image encryption
techniques are evolving, hence fast and secure image security
techniques will always work with high rate of security. We
are doing research work in the field of image security. Image
security techniques should be such that any unauthorized user
cannot access the image and if any modifications can be made
to the image, that modifications can be detected at the
receiving side. Hashing is a good technique that can be used
to verify integrity of the image. Along with hashing, if proper
encryption is provided to the image, the image will be more
secure. Using encryption, any unauthorized user cannot
access the image. Hence, to improve the image security,
proper combination of encryption as well as authentication
techniques presents ideal alternative. To achieve high level of
image security, we are functioning on a hybrid technique
based on image encryption and authentication. The technique
consists of hash generation of the plain image. The generated
hash is embedded in the image and the entire image is
encrypted using combination of chaotic maps and
substitution-diffusion techniques. The technique can provide
high level security to the image with less computation
overheads.
REFERENCES
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[2] Amitesh Singh Rajput, "Towards the Growth of Image Encryption and
Authentication Schemes, "2013 International Conference on Advances
in Computing, Communications and Informatics, P.N.454-459.
[3] Mrs.G.Prema, S.Natarajan, "Steganography using Genetic Algorithm
along with Visual Cryptography for Wireless Network Application"
[4] Tawfiq S. Barhoom, Zakaria M. Abusilmiyeh, "A Novel Cryptography
Method Based on Image for Key Generation", In "2013 Palestinian
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[5] M. Sabery.K, M.Yaghoobi, “A New Approach for Image encryption
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6. www.ijeee-apm.com International Journal of Electrical & Electronics Engineering 19
[14] Narendra K. pareek, Vinod Patidar and K. K. Sud, “Diffusion-
Substitution bsed gray image encryption scheme”, Digital Signal
Processing, Volume 23, Issue 3, May 2013, pages 894-901.
AUTHORS
First Author– Abhishek Thakur: M.
Tech. in Electronics and
Communication Engineering from
Punjab Technical University, MBA
in Information Technology from
Symbiosis Pune, M.H. Bachelor in
Engineering (B.E.- Electronics) from
Shivaji University Kolhapur, M.H.
Five years of work experience in
teaching and one year of work experience in industry. Area of
interest: Digital Image and Speech Processing, Antenna
Design and Wireless Communication. International
Publication: 7, National Conferences and Publication: 6, Book
Published: 4 (Microprocessor and Assembly Language
Programming, Microprocessor and Microcontroller, Digital
Communication and Wireless Communication). Working
with Indo Global College of Engineering Abhipur, Mohali,
P.B. since 2011.
Email address: abhithakur25@gmail.com
Second Author – Rajesh Kumar
is working as Associate Professor
at Indo Global College of
Engineering, Mohali, Punjab. He
is pursuing Ph.D from NIT,
Hamirpur, H.P. and has completed
his M.Tech from GNE, Ludhiana,
India. He completed his B.Tech
from HCTM, Kaithal, India. He
has 11 years of academic
experience. He has authored many research papers in reputed
International Journals, International and National conferences.
His areas of interest are VLSI, Microelectronics and Image &
Speech Processing.
Email address: errajeshkumar2002@gmail.com
Third Author – Amandeep Batth: M. Tech. in Electronics
and Communication Engineering from Punjab Technical
University, MBA in Human
Resource Management from
Punjab Technical University ,
Bachelor in Technology (B-Tech.)
from Punjab Technical University .
Six years of work experience in
teaching. Area of interest: Antenna
Design and Wireless
Communication. International
Publication: 1, National Conferences and Publication: 4.
Working with Indo Global College of Engineering Abhipur,
Mohali, P.B. since 2008.
Email address: amandeep_batth@rediffmail.com
Forth Author – Jitender Sharma: M. Tech. in Electronics and
Communication Engineering from Mullana University,
Ambala, Bachelor in Technology (B-Tech.)from Punjab
Technical University . Five years of work experience in
teaching. Area of interest:, Antenna Design and Wireless
Communication. International Publication: 1 National
Conferences and Publication:6 and Wireless
Communication). Working with Indo Global college since
2008.
E-mail address:er_jitender2007@yahoo.co.in