Secure Schematic Model for Verifying Encrypted Image using

International Journal of Computer Applications (0975 – 8887)
International conference on Green Computing and Technology, 2013
Secure Schematic Model for Verifying Encrypted Image using
Invariant Hash Function
Smita R. Chunamari
D. G. Borse
Dept of. Computer Egineering
A. C. Patil College of Egineering Kharghar
Navi Mumbai, India
Dept. of Electronic and Telecommunication
A. C. Patil College of Egineering Kharghar
Navi Mumbai, India
ABSTRACT
In post globalization era of computer networks and
communication, image and video plays a significance role; rather
the fashion of text based systems will be replaced by the image
based system. The associated threats and challenges related to
image security and its authentication is an active research issues. In
order to ensure a full proof security mechanism for image the
notion of message authentication code for data authentication and
notion of encryption for preserving confidentiality need to be
combined. In this paper a complete frame work of crypto-system
has been proposed, where the parameterization of hash value of
encrypted image is done in such a way that it should be exactly
same with zero difference error of hash value that of the parent
unencrypted original image. It will have enormous scope into
various medical imaging systems where privacy preservation is an
important issue. Designing parametric hashing algorithm, which is
invariant to encryption only by accepting small part of statistical
signature of the original unencrypted image to emerge despite the
encryption process is a non trivial task. The proposed work
formulates authentication of encrypted data by using notion of
authentication code and a novel but yet simple hashing algorithm
which are usable with encrypted image s. The implementation
results of various images, where the hash value is being computed
without the decryption of the original input image, thus validates
the authentication without compromising the privacy information.
Since the hash value is computed without decrypting the original
data, one can prove authenticity without actually revealing the
information.
Keyword
Image Encryption, Hash Function, Encryption, Secure Key.
1. INTRODUCTION
The presence of computer networks has prompted new problems
with security and privacy. Having a secure and reliable means for
communicating with images and video is becoming a necessity and
its related issues must be carefully considered. Hence, network
security and data encryption have become important. The images
can be considered nowadays, one of the most usable forms of
information. Image and video encryption have applications in
various fields including Internet communication, multimedia
systems, medical imaging, telemedicine and military
communication [1][2][3]. There are two types of applications for
information transmission over the Internet. The first ones are the
online applications, which consider the speed as the main issue.
The second ones are web pages, which consider the security as the
main issue. [4][5]. The security mechanisms which are employed
to protect the multimedia data from unauthorized operations are (1)
Multimedia encryption to prevent eavesdropping, (2)
Watermarking for copyright protection and tracking and (3)
Parametric multimedia hashing for content authentication.
Recently, with the greater demand for digital world, the security of
digital images has become more and more important since the
communications of digital products over open network occur more
and more frequently [2, 3, 6]. Surveys of the existing work on
image encryption were also gave general guideline about
cryptography and concluded that all techniques were useful for
real-time image encryption. Techniques described in those studies
can provide security functions and an overall visual check, which
might be suitable in some applications. So no one can access the
image which transferring on open network. Multimedia encryption
and multimedia authentication schemes serve two different
purposes but they can be merged together in one system to protect
confidentiality and to check the authenticity of the data.
Multimedia hashing is another method employed for authenticating
the messages. Hashing is essentially a many-to one mapping which
is used to authenticate the message and to ensure that it came from
the true source. They are also called as one-way functions because
given a message
and a hash function , it is very easy to
compute the hash ℎ = ( ) but given the hash ℎ, it is impossible to
compute such that ℎ = ( ). The robustness requirement of the
hash against manipulations is different for content authentication
and copyright protection applications as it is for watermarks. The
former requires the hash to be fragile against even minute
manipulations while the later requires it to be robust even against
major manipulations.
The proposed paper discusses about the image authentication and
encryption. The section II gives an overview of related work which
identifies all the major research work being done in this area.
Section III highlights about the image encryption considered in
previous research work. Proposed system is discussed in Section
IV followed by implementation and results in Section V. Finally
section VI gives the conclusion of proposed work and the future
extensible work to be done.
2. RELATED WORK
In the digital world nowadays, the security of digital image has
become more and more important because of the advances in
communication technology and multimedia technology. We can
realize that more and more researches have been developed for
security issues to protect the data from possible unauthorized
instructions [6].The security of digital images involves several
different aspects, including copyright protection, authentication,
confidentiality, and access control. Generally, the copyright
protection is addressed by digital watermarking, which embeds the
owner's private information, called the watermark, into the original
image and extracts it from a questionable image when the
ownership needs to be resolved. On the other hand, content
confidentiality
and
39
International Journal of Computer Applications (0975 – 8887)
International conference on Green Computing and Technology, 2013
access control are addressed by encryption, through which only
authorized parties holding encryption keys can access content in
clear text [7, 8]. In this regard, a direct solution is to use an
encryption algorithm to encrypt the data, directly. This solution has
led to the number-theory-based encryption algorithms such as the
Data Encryption Standard (DES), AES, which is a symmetric
encryption algorithms and the RSA algorithm, developed by
Rivest, Shamir and Adleman, which is an asymmetric encryption
algorithm [9][10][11].
However, these encryption schemes appear not to be ideal for
image applications, due to some intrinsic features of images such
as the bulk data capacity and high redundancy, which are
troublesome for traditional encryption. Moreover, these encryption
schemes require extra operations on compressed image data,
thereby demanding long computational time and high computing
power. In real-time communications, due to their low encryption
and decryption speeds, they may introduce significant latency [12].
Innovative encryption techniques need to be developed for
effective data encryption for financial institutions, E-commerce,
and multimedia applications. For future Internet applications on
wireless networks, encryption techniques for multimedia
applications need to be studied and developed. In this thesis, we
focus on the subject of image encryption. Obviously it can be seen
that majority of the work is carried out on image encryption.
3. IMAGE ENCRYPTION
The basic idea of encryption is to modify the message in such a
way that only a legal recipient can reconstruct its content. A
discrete-valued cryptosystem can be characterized by:

a set of possible plaintexts, P.

a set of possible cipher texts, C.

a set of possible cipher keys, K.

a set of possible encryption and decryption
transformations, E and D.
An encryption system is also called a cipher, or a cryptosystem.
The message for encryption is called plaintext, and the encrypted
message is called ciphertext. Denote the plaintext and the
ciphertext by P and C, respectively. The encryption procedure of a
cipher can be described as:
C = Eke (P)
where Eke is the encryption key and E is the encryption function.
Similarly, the decryption procedure is defined as:
P = Dkd (C)
where Dkd is the decryption key and D is the decryption function.
The security of a cipher should only rely on the decryption key Dkd,
since an adversary can recover the plaintext from the observed
ciphertext once he/she gets Dkd. Figure 1 shows a block diagram
for encryption/decryption of a cipher.
ke
kd
Cryptographic algorithms shuffle and diffuse data by rounds of
encryption, while chaotic maps spread the initial region over the
entire phase space via iterations. Permutations are important
mathematical building blocks for symmetric encryption systems in
general, and block ciphers in particular. Permutation is a bijective
map whose domain and range are the same. Permutation ciphers
based on chaos have been proposed [13].
Let be a set. A map : → is a permutation iff is bijective (i.e.
injective and subjective). The set of all permutations of
is
denoted by
→ . We employ a permutation cipher based on
the Cat map. The Cat map is given by,
 xn 1 
y  =
 n 1 
1
q

p 
pq  1

 xn 
y 
 n
mod N
where, and
represent the rows and columns of the data points
respectively, N is the number of columns in data block to be
permuted. We have taken a block size of 16 × 16 where the data
points are actually the DCT coefficients of the image.
The Cat map is employed for a number of iterations for each
16×16 block. The secret key decides the number of iterations for
which Cat map will be employed for each block. The secret key
also decides the values of parameters and . In our simulations,
we have considered 256×256 image. So, in total we are having 256
blocks on which Cat map has to be employed. The inverse Cat map
for decryption is given by,
 x n   pq  1
 y  =  q
 n 
 p   x n 1 


1
  y n 1 
mod N
4. TECHNIQUES OF IMAGE ENCRYPTION
The various techniques of image encryption found in literature till
now are classified as following:
 Modified AES Based Algorithm for Image encryption (2007):
M. Zeghid, M. Machhout, L. Khriji, A. Baganne, and R. Tourki
[14] analyze the Advanced Encryption Standard (AES), and in
their image encryption technique they add a key stream
generator (A5/1, W7) to AES to ensure improving the encryption
performance.
 Image
Encryption Using Block-Based Transformation
Algorithm (2008): Mohammad Ali Bani Younes and Aman [15]
introduce a block-based transformation algorithm based on the
combination of image transformation and a well known
encryption and decryption algorithm called Blowfish. The
original image was divided into blocks, which were rearranged
into a transformed image using a transformation algorithm, and
then the transformed image was encrypted using the Blowfish
algorithm. Their results showed that the correlation between
image elements was significantly decreased. Their results also
show that increasing the number of blocks by using smaller
block sizes resulted in a lower correlation and higher entropy.
 An
information
Encrypted
information
Encryption
Decryption
Recovered
information
Fig 1 Encryption/Decryption of cipher
Classical encryption algorithms are sensitive to keys, while chaotic
maps are sensitive to initial conditions and parameters.
Image Encryption Approach Using a Combination of
Permutation Technique Followed by Encryption (2008):
Mohammad Ali Bani Younes and Aman Jantan [16] introduce a
new permutation technique based on the combination of image
permutation and a well known encryption algorithm called
RijnDael. The original image was divided into 4 pixels × 4
pixels blocks, which were rearranged into a permuted image
using a permutation process, and then the generated image was
encrypted using the RijnDael algorithm. Their results showed
that the correlation between image elements was significantly
decreased by using the combination technique and higher
entropy was achieved.
40
International Journal of Computer Applications (0975 – 8887)
International conference on Green Computing and Technology, 2013
 Image
Encryption Using Self-Invertible Key Matrix of Hill
Cipher Algorithm (2008): Saroj Kumar Panigrahy,
Bibhudendra Acharya and Debasish Jena [17] present image
encryption technique using the Hill cipher. They are generating
self-invertible matrix for Hill Cipher algorithm. Using this key
matrix they encrypted gray scale as well as colour images. Their
algorithm works well for all types of gray scale as well as colour
images except for the images with background of same gray
level or same color.
 Image
Encryption Using Advanced Hill Cipher Algorithm
(2009): Bibhudendra Acharya, Saroj Kumar Panigrahy, Sarat
Kumar Patra, and Ganapati Panda [18] have proposed an
advanced Hill (AdvHill) cipher algorithm which uses an
Involutory key matrix for encryption. They have taken different
images and encrypted them using original Hill cipher algorithm
and their proposed AdvHill cipher algorithm. And it is clearly
noticeable that original Hill Cipher can’t encrypt the images
properly if the image consists of large area covered with same
colour or gray level. But their proposed algorithm works for any
images with different gray scale as well as color images.
 Digital
image encryption algorithm based on chaos and
improved DES (2009): Zhang Yun-peng, Liu Wei, Cao Shuiping, Zhai Zheng-jun, Nie Xuan and Dai Wei-di [19] researches
on the chaotic encryption, DES encryption and a combination of
image encryption algorithm. In their technique firstly, new
encryption scheme uses the logistic chaos sequencer to make the
pseudo-random sequence, carries on the RGB with this sequence
to the image chaotically, then makes double time encryptions
with improvement DES.Their result show high starting value
sensitivity, and high security and the encryption speed.
 New
modified version of Advance Encryption Standard
based algorithm for image encryption (2010): Kamali S.H.,
Shakerian R.,Hedayati M. and Rahmani M.[20] analysis
Advance Encryption Standard(AES) algorithm and present a
modification to the Advanced Encryption Standard (MAES) to
reflect a high level security and better image encryption. Their
result so that after modification image security is high. They also
compare their algorithm with original AES encryption algorithm.
 Image
Encryption Using Affine Transform and XOR
Operation (2011): Amitava Nag, Jyoti Prakash Singh, Srabani
Khan, Saswati Ghosh, Sushanta Biswas, D. Sarkar and Partha
Pratim Sarkar [21] propose a two phase encryption and
decryption algorithms that is based on shuffling the image pixels
using affine transform and they encrypting the resulting image
using XOR operation. They redistribute the pixel values to
different location using affine transform technique with four 8bit keys. The transformed image then divided into 2 pixels x 2
pixels blocks and each block is encrypted using XOR operation
by four 8-bit keys. The total key size used in algorithm is 64 bit.
Their results proved that after the affine transform the
correlation between pixel values was significantly decreased.
 Permutation
based Image Encryption Technique (2011):
Sesha Pallavi Indrakanti and P.S.Avadhani [22] proposes a new
image encryption algorithm based on random pixel permutation
with the motivation to maintain the quality of the image. The
technique involves three different phases in the encryption
process. The first phase is the image encryption. The second
phase is the key generation phase. The third phase is the
identification process. This provide confidentiality to color
image with less computations Permutation process is much quick
and effective. The key generation process is unique and is a
different process.
 Image
Encryption using Chaotic Maps and DNA Addition
Operation and Noise Effects on it (2011): Kuldeep Singh and
Komalpreet Kaur[23] are compared four chaotic maps Cross
chaotic, Logistic, Ikeda and Henon map and noise effects are
observed on image. Firstly, they use the image encryption
algorithm to convert original image to encrypted image. Then
they apply noise on the encrypted image and then decrypt cipher
image with noise back to original image. They have found out
that cross chaotic map showed best results than other three
chaotic maps.
 Image
Encryption Based on the General Approach for
Multiple Chaotic Systems (2011): Qais H. Alsafasfeh and
Aouda A. Arfoa[24] proposed new image encryption technique
based on new chaotic system by adding two chaotic systems: the
Lorenz chaotic system and the Rössler chaotic system. From
Experimental analysis they demonstrate that the image
encryption algorithm has the advantages of large key space and
high-level security, high obscure level and high speed.
 Image Encryption Using Differential Evolution Approach In
Frequency Domain (2011): Ibrahim S I Abuhaiba and Maaly A
S Hassan[25] present a new effective method for image
encryptionwhich employs magnitude and phase manipulation
using Differential Evolution (DE) approach. They have carried
out key space analysis, statistical analysis, and key sensitivity
analysis to demonstrate the security of the new image encryption
procedure.
 Statistical analysis of S-box in image encryption applications
based on majority logic criterion (2011): Tariq Shah, Iqtadar
Hussain, Muhammad Asif Gondal and Hasan Mahmood[26]
propose a criterion to analyze the prevailing S-boxes and study
their strengths and weaknesses in order to determine their
suitability in image encryption applications. The proposed
criterion uses the results from correlation analysis, entropy
analysis, contrast analysis, homogeneity analysis, energy
analysis, and mean of absolute deviation analysis. These
analyses are applied to advanced encryption standard (AES),
affine-power-affine (APA), gray, Lui J, residue prime, S8 AES,
SKIPJACK, and Xyi Sboxes.
5. PROPOSED SYSTEM
In recent the protection of data is required while sending the data in
the network. The proposed system highlights a secure image
encryption and authenticating the encrypted data. The proposed
algorithm calculates hash value of data (image) so that the
encryption process remains transparent to the Hash function. The
Model of navigation, in order to showcase the complete framework
of encryption-description of an image is as below shown in figure
number. A hash function h(m) is a message digest; in some sense,
the message is condensed. Hash functions are routinely used to
check integrity or for error detection of transmitted messages. Hash
functions should accept messages of any length as input, produce a
fixed-length output, and be fast. Message authentication codes
(MAC) check both integrity and authenticity. MACs require the
parties in the communication to agree on an algorithm and possess a
secret key. The MAC algorithm uses the secret key and the message
as input, and it outputs a message authentication code.
The mathematical representation of the hash calculated using the
plaintext data and the encrypted data will remain the same and can
be represented as given below in the equation
Hash (Enc (msg, Ek), Kh) = Ha(msg, Kh)
Where, msg the message to be transmitted, Enc is the encryption
function, Ek the encryption key, ℎ the hashing key and a the
hashing algorithm. It also to be ensure that
Hash (Enc (msg, Ek1), Kh) = Hash (Enc (msg, Ek2), Kh)
41
International Journal of Computer Applications (0975 – 8887)
International conference on Green Computing and Technology, 2013
Where, Ek1 and Ek2 are two encryption keys. To start with, first to
compute the 16x16 block Discrete Cosine Transform (DCT) of the
image. In order to do that, first divide the image into blocks each of
dimension of order 16x16 and after dividing there will be total 256
such blocks. For the Nth block IN the 2-dimensional DCT DN is
given as,
15 15
 (2mH )i
m 0 n 0
2M
DN  ai a j  I Nij cos
cos
 (2nH ) j
2N
Where 0  i  15,0  j  15 and
 1

 1

i0 
j0 
 4
 4
 and

ai  
ai  


1
1
1  i  15

1  j  15

 8
 8


After calculating the DCT coefficients for each block and then
apply the Cat map individually to each of the block. The secret key
decides the values of the parameters and and the number of
iterations for which Cat map will be employed for each of the
block. Applying a permutation cipher which scrambles only the
positions of the DCT coefficients within the block, the statistics of
the block like its mean and variance remain the same. So, in order
to generate the hash, select the means and variances of the blocks
as proposed feature space. This feature space remains invariant to
the encryption process. Hence, the hash of the original image and
the scrambled image remain the same. The mean of the Nth block
DN is given by,
meanDN 
1 15 15
 DN (i, j)
256 i 0 j 0
The means and the variances are normalized using the following
equations,
2
15 15
varDN  {DN (i, j )  meanD }
N
i 0 j 0
norm _ meanDK 
norm _ varDK 
meanDK
max
k {1,2,..256}{meanDK }
varDK
max
k {1,2,..256}{varDK }
Prime
Modules
Image
Encryption
Image
Decryption
Fig 3 Process Flow Diagram of Proposed System
The complete process flow (Figure 2) of encryption and generation
of hash is as shown in figure 3:
Fig 2 Modules of the proposed system.
Cryptographic hash functions and block ciphers are often used to
construct MAC algorithms. The modules of the proposed system is
as shown in Figure 2:
So, by using above equations the feature space the normalized
means and variances of 256 blocks where, norm_meanDK and
mean_varDK ϵ(0, 1). Next to sort out the blocks based upon the
increasing values of the normalized variances. ℎ has two
components- ℎ1 and ℎ2.The top n blocks are selected based upon
the secret key ℎ1. The means and variances of the selected blocks
are then quantized.
42
International Journal of Computer Applications (0975 – 8887)
International conference on Green Computing and Technology, 2013
Suppose one of the normalized mean values is 0.7924. The binary
equivalent of 0.7924 is 0.11001010110110101. The bit patterns
that obtain after quantizing the variance and mean are concatenated
together. The concatenated bit patterns obtained for each block are
stacked together in a vector then, using the key ℎ2, can generate
the random sequence between 0 and 1 of length 100. Then,
multiply each of the random number with the size of vector and
round off the products. The bits corresponding to the indices
indicated by the rounded-off products are selected from the vector
. This is the required hash.
16 * 16 Block
Encrypted Image
Saving
Hash Function
Saving
The above calculations are done for the images and the encrypted
data and the resultant hashes are found to be the same as shown in
Figure 4.
a
Input Image
Hash Image
Division
16 x 16 Blocks
Mean Value
Secret Key
Variable Value
Encryption of
Image
ENCRYPTED Image
Display
Hash function
ENCRYPTED Hash
Image Display
Fig 5 Architectural Schema of Encryption Process.
b
Encrypted Image
Display ENCRYPTED Image
Hash Function Encrypted Data
Selection of Hash Function
Input Hash Function
Authentication
Difference with ERROR
c
Secret Key
d
Decryption
Display Decrypted Image
Fig 6 Architectural Schema of Decryption
6. IMPLEMENTATION & RESULTS
In order to show the credibility of the proposed algorithm, it can be
tested across a variety of images such that:

Fig 4. Results showing the validity of the proposed algorithm.
Figure 4 shows the hash of the original image and the encrypted
image are same. (a) is the Original Lena image, (b) is the Hash
derived from Original Lena image, (c) is the Encrypted Lena
image, (d)shows the Hash derived from Encrypted Lena image.
The complete architecture is shown in Figure 5 and the
complete process flow of decryption with hash function framework
is as shown in Figure 6:
The entire process of decryption is just a reversible process of
encryption being performed. The user will require encrypted
image, encrypted hash image and secret key to perform decryption.
The architectural diagram of decryption process is as shown into
the Figure 6

The hash value is unique to a given image. Different images
should yield significantly different hash values. If the distance
between hash values from two different images are
significantly different, this can be used as a means of indexing
the respective images.
The hash invariance to encryption must be verified for
different images in order to justify this generalization.
The implementation of the proposed work is shown in Figure 8 and
Figure 9. For each image, first compute the 16 × 16 block DCT.
Then, each block is encrypted. Chaos encryption based on Cat map
has been employed. The key Ek decides the values of p, q and the
number of times the Cat map will be iterated for each of the blocks.
The security is strong because not only the parameters p, q are
decided by the key but proposed work also have randomized the
number of iterations for the Cat map.
The next step is to calculate the hash value of the original image
and its corresponding encrypted version. As expected, they are
found to be the same. The hashes obtained for each of the images
are of 100 bits length. It can also be verified that the Hash for any
image obtained from the proposed algorithm is unique. It can be
ensured by finding the hamming distance between the hashes of
different images and then XOR the two hashes.
43
International Journal of Computer Applications (0975 – 8887)
International conference on Green Computing and Technology, 2013
also depicts a significant variability across a variety of images.
Future work entails developing hashes for much stronger ciphers.
Decrypted hash function
Decrypted image
16X16 blocks
Enter key
Original image
Fig 9 Decryption of the image
Fig 7 Results of Decryption
Original image
Hash function
Mean values
8. REFERENCES
Variance values
[1] O. S. Faragallah, Utilization of Security Techniques for
Multimedia Applications , Ph. D. Thesis, Department of
Computer Science and Engineering, Faculty of Electronic
Engineering, Menofia University, 2007.
[2] A. J. Menezes, P. C. V. Oorschot and S. Vanstone, Handbook
of Applied Cryptography, CRC Press Boca Raton,USA, 1996.
Encrypted image
16X16 blocks
Encrypted hash function
Enter key
[3] L. Qiao, Multimedia Security and Copyright Protection , Ph.
D. Thesis, Department of Computer Science, University of
Illinois at Urbana-Champaign, Urbana, Illinois, USA, 1998.
[4] W. Stallings, Cryptography and Network Security: Principles
and Practice, Prentice- Hall Upper Saddle River, USA, 1999.
[5] C. E. Shannon, Communication Theory of Secrecy Systems,
Bell System Technical Journal, Vol. 28, No. 4, pp. 656-715,
October 1949.
Fig 8 Encryption of original image and the hash functions.
[6] S. Li, G. Chen and X. Zheng, Chaos-Based Encryption for
Digital Images and Videos, Chapter 4 in Multimedia Security
Handbook, CRC Press LLC, February 2004.
The Figure 8 explains about the original image and its hash
function, mean values, variance values and next it converted to a
16x16 block and enter the secret key. After entering the secret key
the encrypted hash function and the encrypted original image are
shown.
[7] Y. Mao and M. Wu, A Joint Signal Processing and
Cryptographic Approach to Multimedia Encryption, IEEE
Transactions on Image Processing, Vol. 15, No. 7, pp. 20612075, July 2006.
The Figure 7 and Figure 9 explains about the decryption of the
image, while in decryption first step is to enter the secret key and
then the decrypted hash function and the encrypted image is
generated and in next again converted to 16x16 block to retrieve
the original image.
7. CONCLUSION
This paper discusses about a new framework for authenticating
encrypted images. By allowing a portion of the statistical signature
in the original image to surface despite the encryption operation, it
becomes possible to validate the authenticity of the encrypted
image without tapping into its contents. By constraining the
encryption process to be a block DCT permutation cipher, it has
been observed that the mean and variances of the blocks remain the
same even after encryption. The proposed work has used these two
features to construct the hash value. This simple choice of features
[8] Y. Mao, Research on Chaos-Based Image Encryption and
Watermarking Technology, Ph. D. Thesis, Department of
Automatation, Nanjing University of Science & Technology,
Nanjing, China, August 2003.
[9] J. Daemen and V. Rijmen, AES Proposal: Rijndael, AES
Algorithm Submission, 1999.
[10] R. L. Rivest, M. J. B. Robshaw, R. Sidney, and Y. L. Yin, The
RC6TM Block Cipher , M. I. T laboratory for Computer
Science, 545 Technology Square, Cambridge, MA 02139,
USA, 1998.
[11] R. F. Sewell, Bulk Encryption Algorithm for Use with RSA ,
Electronics Letters , Vol. 29, No. 25, pp. 2183-2185, 9 Dec.
1993.
[12] H. E. H. Ahmed, H. M. Kalash, and O. S. Faragallah,
Encryption Efficiency Analysis and Security Evaluation of
RC6 Block Cipher for Digital Images , International
44
International Journal of Computer Applications (0975 – 8887)
International conference on Green Computing and Technology, 2013
Conference on Electrical Engineering (ICEE '07), pp. 1-7, 1112 April 2007.
[13] Z. Lv, L. Zhang, and J. Guo, “A Symmetric Image Encryption
Scheme Based on Composite Chaotic Dispersed Dynamics
System,” Proc. Of Second Symposium on Computer Science
and Computational Technology, pp. 191–194, 2009.
[14] M. Zeghid, M. Machhout, L. Khriji, A. Baganne, R. Tourki,
―A Modified AES Based Algorithm for Image Encryption‖,
World Academy of Science, Engineering and Technology 27
2007.
[20] Kamali, S.H., Shakerian, R., Hedayati, M.,Rahmani, M., A
new modified version of Advance Encryption Standard based
algorithm for image encryption, Electronics and Information
Engineering (ICEIE), 2010 International Conference.
[21] Amitava Nag, Jyoti Prakash Singh, Srabani Khan, Saswati
Ghosh, Sushanta Biswas, D. Sarkar Partha Pratim Sarkar,
―Image Encryption Using Affine Transform and XOR
Operation‖, International Conference on Signal Processing,
Communication, Computing and Networking Technologies
(ICSCCN 2011).
[15] Mohammad Ali Bani Younes and Aman Jantan ―Image
Encryption Using Block-Based Transformation Algorithm‖
IAENG International Journal of Computer Science, 35,2008.
[22] Sesha Pallavi Indrakanti, P.S.Avadhani, Permutation based
Image Encryption Technique, International Journal of
Computer Applications (0975 – 8887) Volume 28– No.8,
2011.
[16] Mohammad Ali Bani Younes and Aman Jantan, ―An Image
Encryption Approach Using a Combination of Permutation
Technique Followed by Encryption‖, IJCSNS International
Journal of Computer Science and Network Security, VOL.8 ,
April 2008.
[23] Kuldeep Singh, Komalpreet Kaur, Image Encryption using
Chaotic Maps and DNA Addition Operation and Noise Effects
on it‖, International Journal of Computer Applications (0975 –
8887) Volume 23– No.6, June 2011.
[17] Saroj Kumar Panigrahy, Bibhudendra Acharya and Debasish
Jen‖, Image Encryption Using Self-Invertible Key Matrix of
Hill Cipher Algorithm 1st t International Conference on
Advances in Computing, Chikhli, India, 21-22 February 2008.
[18] Bibhudendra Acharya, Saroj Kumar Panigrahy, Sarat Kumar
Patra, and Ganapati Panda, Image Encryption Using
Advanced Hill Cipher Algorithm, International Journal of
Recent Trends in Engineering, Vol. 1, No. 1, May 2009.
[19] Zhang Yun-peng, Liu Wei, Cao Shui-ping, Zhai Zheng-jun,
Nie Xuan , Dai Wei-di, Digital image encryption algorithm
based on chaos and improved DES‖, IEEE International
Conference on Systems, Man and Cybernetics, 2009.
IJCATM : www.ijcaonline.org
[24] Qais H. Alsafasfeh , Aouda A. Arfoa, Image Encryption
Based on the General Approach for Multiple Chaotic Systems,
Journal of Signal and Information Processing, 2011.
[25] Ibrahim S I Abuhaiba, Maaly A S Hassan, ―Image
Encryption Using Differential Evolution Approach In
Frequency Domain‖ Signal & Image Processing: An
International Journal (SIPIJ) Vol.2, No.1, March 2011.
[26] Tariq Shah, Iqtadar Hussain, Muhammad Asif Gondal , Hasan
Mahmood, Statistical analysis of S-box in image encryption
applications based on majority logic criterion, International
Journal of the Physical Sciences Vol. 6(16), pp. 4110-4127,
18 August, 2011
45