International Journal of Engineering Trends and Technology (IJETT) – Volume 17 Number 1 – Nov 2014
A Hybrid Approach of Image Encryption and
Compression for Secure Transmission
Posa Naga Lavanya Yedida1, P. Ravi Kiran2
1
Final M.Tech Student ,2 Associate Professor
Dept of CSE, Swarnandhra College Engineering and Technology, Seetharampuram,W.G.Dt,[A.P],India
1,2
Abstract: In addition to provide the security for data
through image, we are using the concepts hybrid approach
of encryption and compression techniques, before
transmission of data we can encrypt it by using
cryptographic technique. In this paper we are using triple
DES algorithm for data encryption and decryption, after
encryption of data the cipher data can be stored into image
using LSB technique and image can be encrypted by using
PTT(pixel transpose technique),after encryption ,image can
be compressed by using Arithmetic compression and
decompression technique.
Our proposed architecture
provides data confidentiality and improves the performance
than traditional approaches.
I. INTRODUCTION
In previous days transfer the image and data through
network in form of plain format. So that transferring data
and image in form of plain is will loss the security in a
network. So that we can provide the security the
transferring image and data can be sent in form of
unknown format. So that by convert data and image into
unknown format we can encrypt image by using any
technique.[1,5]
The main aim of encoding or encryption is to
provide the confidentiality over the communication and
storage process. In present days the usage is considered as
particular devices that consider extra features those are
calculations over authorized computers. For this use
unauthorized nodes is only the encoded version of the data
in the process. The nodes will calculation on the encoded
data without having any knowledge on the real value.
Lastly the data send back and decrypt the data. [4]
The most well-known cryptosystems are
deterministic: for a fixed encryption key, a given plain text
will always be encrypted in the same ciphertext. This may
lead to some drawbacks.RSA is a good example to
illustrate this point:
(i) Particular plain texts may be encrypted in a too much
structured way: with RSA, messages 0 and 1 are always
encrypted as 0 and 1, respectively;
(ii) it may be easy to compute partial information about the
plaintext: with RSA, the cipher text c leaks one bit of
Whereas the development of tools capable of
processing encrypted signals may seem a formidable task,
some recent,still scattered, studies, spanning from secure
embedding and detection of digital watermarks and secure
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information about the plain text m, namely, the so called
Jacobi symbol;
(iii) when using a deterministic encryption scheme, it is
easy to detect when the same message is sent twice while
processed with the same key.
Coming to security issues the encryption schemes are
formatted for initial time and it introduced an author
Shannon that is best method to provide perfect secrecy
which the encoding methods are not given any information
about plain text or about key. In this method it is proved
that one time pad that is successfully protected under some
particular conditions.
This model has allowed the study of the security level for
numerous asymmetric ciphers. Recent works show that we
are now able to perform proofs in a more realistic model
called the standard model. From [2] to [3], a lot of papers
compared these two models, discussing the gap between
them. In parallel with this formal estimation of the security
level, an empirical one is performed in any case, and new
symmetric and asymmetric schemes are evaluated
according to published attacks.
II. RELATEDWORK
In recent studies the digital signaling is enabled in
many number of applications. It is introduced in
multimedia systems and these services are using in secret
communication. Present technical solutions are secure
modifications of the data using cryptographic methods
using secure network layer techniques. That is for
protecting data at the time of transferring the data. This
tends to the cryptographic layer features by generating to
protect the unauthorized access of the users. It is for
providing the authorize access in the network for data
access.[7,8]
It is clear that the availability of signal processing
algorithms that work directly on encrypted signals would
be ofgreat help for application scenarios where signals
must be produced, processed, or exchanged securely.
content distributionto compression of encrypted data and
access to encrypted databases, have shown that performing
signal processing operations in encrypted content is indeed
possible.[6]
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International Journal of Engineering Trends and Technology (IJETT) – Volume 17 Number 1 – Nov 2014
III. PROPOSED SYSTEM
User A key generation:
Now a day’s transmission of data through image over
network without losing data integrity is a complex task. To
provide security of data and image, we can use the
cryptography techniques, image encryption and decryption
technique and compression techniques. In this paper we are
using an efficient technique for provide more security.
User A selects a private key and calculates a public key.
In Cryptographic Module, it is used for convert data
into unknown format. The conversion of data into unknown
format is called encryption and converting cipher text into
plain text is called the decryption, before sending data
through image the sender will encrypt data using Triple
DES algorithm. After converting data into unknown format
that cipher text will be stored into image and sent to
receiver. The receiver will retrieve the cipher text from the
image and decrypt using triple des to retrieve the plain text.
XA<p
Generate public key YA
YA=q
XA
mod p
User B key generation:
User B selects a private key and Calculates a public key.
Select private key XB
XB<p
Generate public key Y B
YB=q
Key Generation algorithm:
Diffie-hellman is one of the key exchange algorithms and
is used for Delta value generation.

Select private key XA
Global public elements:
XB
mod p
Generation of secret key by User A:
This algorithm considers the two public keys:
User A generate a secret key using his private key and User
B public key.
p(prime number)
K=(YB) XA mod p
q(primitive root)
Generation of secret key by User B:
q<p.
User B generate a secret key using his private key and User
A public key.
K=(YA) XB mod p
Store data into image:
(ii)
The sender will receive the cipher text and convert into
binary format. After converting binary format the sender
will store into image by using LSB technique. Before
storing data into image the sender will retrieve each pixel
from the image and convert into binary format after we can
store data into image, after completion of storing data into
image the sender will generate data hide image.
(iii)
POT technique:
After storing data into image the sender will encrypt
and decrypt the image. In this paper the sender and receiver
will use POT technique for image encryption and
decryption. The procedure of POT technique as follows.
(iv)
Then stored all the pixels value of I in two
dimensional array named as P
like every image have rows or column wise
pixels.
Firstly row wise XOR all the bits of pixel from
top to bottom like as firstly XOR first and
second row and then store first row as XOR
Result and second rows as it is than XOR
second and third rows and store as according
to previous operation and then apply to all the
rows.
A square grid of required size constructed by
taking binary data from thexor data.
(V)
1. Encryption process:
(i)
First of all select whole image and give named
as I.
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Now grid transposition applied by reading data
diagonally and writing it down on row basis
from left to right.
(Vi) A new grid generated after transposition.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 17 Number 1 – Nov 2014
(vii) The new grid is converted into ASCII sequence
and written into Image file.
2. Decryption process :
After decompression of image the image can be
converted into pixel and perform the decryption process.
(i)
(ii)
A square grid of required size constructed by
taking binary data from the
Image file.
Now grid transposition applied by reading
data diagonally and writing it down on row
basis from left to right.
(iii)
A new grid generated after transposition.
(iv)
After column wise XOR all the bits of pixel
from right to left like as firstly XOR last and
lase second column until completion of
reverse process encryption. After column xor
again perform the row wise from right to left .
Then stored all the pixels value of I in two
dimensional array named as P
And getting original image.
(v)
Symbol
A
E
I
O
U
!
Probability
.2
.3
.1
.2
.1
.1
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Arithmetic compression technique
Here sender performs the compression technique for image
compression and receiver performs the decompression
technique for image decompression, for performing
compression and decompression we are using arithmetic
technique for image compression and decompression. After
performing of encryption of image the sender will
compress the image using Arithmetic compression
technique and sent to receiver, after sending the receiver
will retrieve the compressed image and decompress by
using the arithmetic decompression technique.
Arithmetic compression technique
To encode a long message into a single code word without
using a large codebook, we must
Step I: use a (hash) function to compute an ID (or tag) for
the message. The function should be invertible
Step II: Given an ID (tag), assign a codeword for it using
simple rules, hence, there is no need to build a large
codebook Arithmetic coding is an example of how these
two steps can be achieved by using cumulative density
function (CDF) as the hash function
In arithmetic coding, each symbol is mapped to an interval
Message: “eaii!”
Interval
[0, 0.2)
[0.2, 0.5)
[0.5, 0.6)
[0.6, 0.8)
[0.8, 0.9)
[0.9, 1.0)
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International Journal of Engineering Trends and Technology (IJETT) – Volume 17 Number 1 – Nov 2014
Tag selection for a message:
Since the intervals of messages are disjoint, we canpick
any values from the interval as the tag
A popular choice is the lower limit of the interval, Single
symbol example: if the mid-point of the interval[FX(ai–1),
FX(ai)) is used as the tag TX(ai) of symbol ai, then
Note that: the function TX(ai) is invertible.
To generate a unique tag for a long message, we need an
ordering on all message sequences
A logical choice of such ordering rule is the lexicographic
ordering of the message With lexicographical ordering, for
all messages of length m, we have
Symbol
1
2
3
4
Fx
.5
.75
.875
1.0
Tx
.25
.625
.8125
.9375
Recursive Computation of Tags:
Assume that we want to code the outcome of rolling a
fair die for three times. Let’s compute the upper and
lower limits of the message “3-2-2.”
For the first out come “3,” we have
l(1) = FX(2), u(1) = FX(3).
For the second outcome “2,” we have upper limit
FX
(2)(32) = [P(x1 = 1) + P(x1 = 2)] + P(x = 31) + P(x = 32)
= FX(2) + P(x1 = 3)P(x2 = 1) + P(x1 = 3)P(x2 = 2)
= FX(2) + P(x1 = 3)FX(2) = FX(2) + [FX(3) –
FX(2)]FX(2).
In Binary
.010
.101
.1101
.1111
Thus, u(2) = l(1) + (u(1) – l(1))FX(2).
Similarly, the lower limit FX
(2)(31) is l(2) = l(1) + (u(1) – l(1))FX(1).
For the third outcome “2,” we have
l(3) = FX
(3)(321), u(3) = FX(3)(322).
Using the same approach above, we have
FX(3)(321) = FX(2)(31) + [FX(2)(32) – FX(2)(31)]FX(1).
FX(3)(322) = FX(2)(31) + [FX(2)(32) – FX(2)(31)]FX(2).
Therefore,
l(3) = l(2) + (u(2) – l(2))FX(1), and u(3) = l(2) + (u(2) –
l(2))FX(2).
In general, we can show that for any sequence x =
(x1x2…xn),
l(n) = l(n–1) + (u(n–1) – l(n–1))FX(xn–1)
u(n) = l(n–1) + (u(n–1) – l(n–1))FX(xn).
If the mid-point is used as the tag, then
Note that we only need the CDF of the source alphabet to
compute the tag of any long messages.
Deciphering The Tag:
The algorithm to deciphering the tag is quite straight
forward:
1. Initialize l(0) = 0, u(0) = 1.
2. For each k, find t* = (TX(x) – l(k–1))/(u(k–1) – l(k–1)).
3. Find the value of xk for which FX(xk – 1) t* FX(xk).
4. Update u(k) and l(k).
5. If there are more symbols, go to step 2.
In practice, a special “end-of-sequence” symbol is used to
signal the end of a sequence.
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Where y < xi means y precedes xi in the ordering of all
messages.Bad news: need P(y) for all y < xi to compute
TX(xi)!
[log* 1/pco]+1
2
3
4
4
Code
01
101
1101
1111
Example of Decoding Tag:
Given A = {1, 2, 3}, FX(1) = 0.8, FX(2) = 0.82, FX(3) = 1,
l(0) = 0, u(0) = 1. If the tag is TX(x) = 0.772352, what is x?
Note:
l(n) = l(n–1) + (u(n–1) – l(n–1))FX(xn–1)
u(n) = l(n–1) + (u(n–1) – l(n–1))FX(xn)
t* = (0.772352 – 0)/(1 – 0) = 0.772352
FX(0) = 0 ≤t* ≤ 0.8 = FX(1)
l(1) =0, u(1) = 0.8.1
t* = (0.772352 – 0)/(0.8 – 0) = 0.96544
FX(2) = 0.82 ≤t* ≤ 1 = FX(3)
l(2) =0.656, u(2) = 0.8.13
t* = (0.772352 – 0.656)/(0.8 – 0.656) = 0.808
FX(1) = 0.8 ≤t* ≤ 0.82 = FX(2)
l(3) =0.7712, u(3) = 0.77408.132
t* = (0.772352 – 0.7712)/(0.77408 – 0.7712) = 0.4
FX(1) = 0 ≤t* ≤ 0.8 = FX(1)1321
Binary Code for the Tag:
If the mid-point of an interval is used as the tag TX(x),a
binary code for TX(x) is the binary representation ofthe
number truncated to l(x) = _log(1/P(x))_ + 1 bits.
_ For example, A = { a1, a2, a3, a4 } with probabilities{
0.5, 0.25, 0.125, 0.125 }, a binary code for each
symbol is as follows
IV. CONCLUSION
We are concluding our current research work with efficient
encryption of image and compression techniques. Data
privacy or confidentiality and can be maintained by Triple
DES cryptographic algorithm and Diffie-hellman key
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International Journal of Engineering Trends and Technology (IJETT) – Volume 17 Number 1 – Nov 2014
exchange protocol.PTT technique encrypts the image and
followed by image compression technique with arithmetic
coding mechanism and vice versa followed by the receiver
decompress the image followed by decryption of image
then retrieves the cipher information and convert to plain
with triple DES algorithm.
REFERENCES
[1] “Methods for subjective determination of transmission quality,” ITUR Recommendation P.800, 1996.
[2] “Methodology for the subjective assessment of the quality of
television pictures,” ITU-R Recommendation BT.500-11, 2002.
[3] I. Avcibas, B. Sankur, and K. Sayood, “Statistical evaluation of image
quality measures,” Journal of Electronic Imaging, vol. 11, no. 2, pp. 206–
223, 2002.
RAVI KIRAN received his B.Tech from
J.N.T.U and M.TECH in Computers &
Communications from JNTU.His areas of
interests include Artificial Intelligence,
Image processing, Speech processing and
Neural networks. He has 8+ years of
experience in teaching to engineering students. He is the
member of C.S.I, (India) and IAENG (U.S.A). He is now
the Associate Professor, Department of C.S.E at
Swarnandhra College of Engineering & Technology;
Narsapur. He is heading Special Interest Research Groups
in Image and Speech processing. He was also listed in
ICGST and ACM. He has published many technical papers
both in international and national Journals & Conferences.
[4] G. Chen, Y.Mao, and C. K. Chui, “A symmetric image encryption
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October 2006.
BIOGRAPHIES
Posa Naga Lavanya Yedida received B.Tech
degree in computer science and engineering
from Jawaharlal Nehuru Technological
university Kakinada, pursuing M.Tech
(computer science and engineering).she is an
p.gstudent, department of computer science and
engineering, Swarnandhra College of Engg, Technology,
Seetharampuram, W.G.Dt(A.P),India. Her area of interest
is Image processing.
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