International Journal of Engineering Trends and Technology (IJETT) – Volume 17 Number 1 – Nov 2014
A Simple and Efficient Framework for Reversible
Data Suppression in Images
Vardhanapu Alekhya1, Kaligithi Rajesh Kumar 2
1,2
Final M.Tech Student1,Associate Professor2
dept of CSE in Swarnandhra College of Engineering & Technology, Seetharampuram, W.G.Dt,[A.P],India
Abstract: Steganography is the efficient method to authenticate
users and sending secret messages in present days. There are
many existing methods for hiding data in image which depends of
the density of the pixels and the color ranges. In many of the
methods in previous research failed to maintain the originality of
the image after hiding of data or message. So we introduced a
novel technique to hide data in image by applying the
cryptographic techniques on the image and the text. In this
technique we mainly use LSB based techniques and symmetric
cryptographic techniques. It reduces the distortion levels of the
image and tried to maintain the original quality of the image.
I. INTRODUCTION
Present days there is increase in network usage.
Many users are communicating and exchanging
information through network. Due to rapid increase of the
data exchange there is increase in malicious users also. For
reducing the malicious attacks there are many researches
done and still the researches are going on for increasing
security over the network. But many of the methods are
failed to reduce and defend over the network. Researchers
focused on many issues such as the data embedding, image
quality, data transferring, and data receiving, extracting
message from the image. [1][2]
Coming to data embedding it is also referred as
data hiding in image there so many techniques such as
encrypting of the message before embedding. In this
concept cryptographic methods are introduced in
steganography techniques. Initially the researchers
introduced a public key cryptographic technique. In this
technique users have to execute key exchanging protocol.
After generating secret keys encrypt the text message and
embed in image pixels.
In there are two main uses of data hiding in media
are to present proof of the copyright and guarantee of data
integrity. So the data mustremain hiddenin a deployed
signal and though the signal is going to modify as
degrading as filtering and re-sampling or lossy content
compression. In some applications the data hiding that is
the consistency of amplification of the data and there is no
need todifferentiate the detection or deleting until these
data are for the profit ofboth the data owner and the user.
So methods used for data hiding different and depends
upon the density of data being hidden and the required
invarianceof the data to modify. The method is not capable
ISSN: 2231-5381
of achieving all these problems and a type of processes
required to length the range of capable applications.
Information concealing routines must be equipped
for installing the information in a sign with the underneath
limitations and properties:
1. The host signal must be consented to debased and the
inserted information must be negligibly noticeable. (The
point is for the information to covered up. As any
entertainer will let you know, it is feasible for something to
be shrouded while it stays in plain sight; you simply keep
the individual from taking a gander at it. We will utilize the
words covered up, imperceptible, unperceivable, and
undetectable to imply that an onlooker does not recognize
the vicinity of the information, regardless of the fact that
they are discernible.)[4]
2. The inserted information must be specifically encoded
into the media, instead of into a header or wrapper, so that
the information stay in place crosswise over differing
information document forms.
3. The inserted information must be safe to adjustments
extending from deliberate and clever endeavors at
evacuation to foreseen controls, e.g., channel commotion,
sifting, resampling, trimming, encoding, lossy layering,
printing and checking, computerized to-simple (D/A)
change, and simple to-advanced (A/D) transformation, and
so on.
4. Unbalanced coding of the inserted information is
attractive, since the motivation behind information stowing
away is to keep the information in the host signal, however
not so much to make the information hard to get to.
5. Slip rectification coding1 must be utilized to guarantee
information trustworthiness. It is certain that there will be
some debasement to the installed information when the
host sign is adjusted.
6. The installed information must act naturally timing or
self-assertively re-contestant. This guarantees that the
installed information can be recuperated when just parts of
the host sign are accessible, e.g., if a sound chomp is
concentrated from a meeting, information implanted in the
sound section can be recouped. This peculiarity
additionally encourages programmed unraveling of the
concealed information; since there is no compelling reason
to allude to the first have signal.
Applications: [5] Exchange offs exist between the
amount of implanted information and the level of
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International Journal of Engineering Trends and Technology (IJETT) – Volume 17 Number 1 – Nov 2014
invulnerability to have signal change. Via compelling the
level of host signal debasement, an information concealing
system can work with either high inserted information
rate,or high imperviousness to alteration, however not both.
As one expands, the other must abatement. While this can
be indicated scientifically for some information concealing
frameworks for example, a spread range, it appears to hold
valid for all information concealing frameworks. In any
framework, you can exchange data transfer capacity for
power by abusing repetition. The amount of inserted
information and the level of host signal alteration differ
from application to application. Hence, distinctive
strategies are utilized for distinctive applications
II.RELATED WORK
The plan is made up of picture encryption,
information inserting and information extraction/picture
recuperation stages. This paper proposes distinguishable
Original
Image
Encryption key
side, the information implanted in the made space can be
effortlessly recovered from the scrambled picture
containing extra information as per the information
concealing key. Since the information inserting just
influences the LSB, a decoding with the encryption key can
bring about a picture like the first form.
Image Encryption process:
While an encoded binary image can be packed
with a lossless way by discovering the disorders of low
density equality check codes, a lossless pressure technique
for scrambled ash image utilizing dynamic decay and rategood punctured turbo codes is created in .With the lossy
layering strategy exhibited in, an scrambled ash image can
be proficiently compacted via tossing the unreasonably
unpleasant and fine data of coefficients produced from
orthogonal change. While having the packed information, a
beneficiary may remake the key substance of unique image
by recovering the estimations of coefficients. The
substance manager scrambles the first uncompressed image
utilizing an encryption key to deliver an encoded image.
Encrypted
Image
Data hiding key
Embed
Data to
embed
Encrypted
Text
Stego
image
reversible information covering up in encoded picture. In
the proposed plan, the first picture is encoded utilizing an
encryption key and the extra information are installed into
the scrambled picture utilizing information stowing away
key.
With a scrambled picture containing extra
information, if the recipient has just the information
concealing key, he can remove the extra information
however collector does not know the picture content. If
recipient has the encryption key, he can decode the got
information to get a picture like the first one, yet can't
separate the inserted extra information The substance
holder scrambles the first uncompressed picture utilizing an
encryption key to create an encoded picture.[6,7]
At that point, the information hider layers the
minimum critical bits (LSB) of the scrambled picture
utilizing an information concealing key to make a scanty
space to oblige the extra information. At the beneficiary
ISSN: 2231-5381
At that point, the information hider layers the
minimum critical bits (LSB) of the scrambled image
utilizing an information concealing key to make a scanty
space to suit the extra information. At the collector side,
the information installed in the made space can be
effortlessly recovered from the scrambled image containing
extra information as indicated by the information
concealing key. Since the information implanting just
influences the LSB, a decoding with the encryption key can
bring about an image like the first form. At the point when
utilizing both of the encryption and information concealing
keys, the installed extra information can be effectively
separated and the first image can be impeccably
recuperated by misusing the spatial connection in
characteristic image.[9]
Data embedding method:
In the information inserting stage, a few
parameters are inserted into a little number of scrambled
pixels, and the LSB of the other encoded pixels are layered
to make a space for obliging the extra information and the
first information at the positions possessed by the
parameters. As indicated by the information concealing
scratch, the information hider pseudo arbitrarily chooses
NP encoded pixels that will be utilized to convey the
parameters for information covering up. Here NP is a little
positive number, for instance Np=20.the other encoded
pixels are pseudo-arbitrarily permuted and partitioned into
number of gatherings, each of which contain L pixels. The
change way is additionally controlled by the information
concealing key. For every pixel-gathering, gather the M
minimum critical bits of the L pixels, and mean them as B
(k,1) , B (k,2) … B(k,m*l) where k is a gathering file
inside [1,(n-Np)/L] and M is a positive whole number
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International Journal of Engineering Trends and Technology (IJETT) – Volume 17 Number 1 – Nov 2014
short of what 5. The information hider additionally creates
a network G measured (M*l – S) * M*l, which is made out
of two sections. The left part is the personality lattice and
the right part is pseudo-irregular binary network inferred
from the information concealing key. For each one
gathering, which is item with the G lattice to structure a
grid of size (M * L-S). Which has scanty bits of size S, in
which the information is installed and organizes the pixels
into the first structure and permutated to structure an
unique im
Image Decryption method:
When having an encrypted image containing
embedded data, a receiver firstly generates ri,j,k according
to the encryption key, and calculates the exclusive-or of the
received data and ri,j,k to decrypt the image. We denote the
Decrypted bits as b1i,j,k . Clearly, the original five most
significant bits (MSB) are retrieved correctly. For a certain
pixel, if the embedded bit in the block including the pixel is
zero and the pixel belongs to S1, or the embedded bit is 1
and the pixel belongs to S0, the data-hiding does not affect
any encrypted bits of the pixel. So, the three decrypted
LSB must be same as the original LSB, implying that the
decrypted gray value of the pixel is correct. On the other
hand, if the embedded bit in the pixel’s block is 0 and the
pixel belongs to S0, or the embedded bit is 1 and the pixel
belongs to S1, the decrypted LSB. That means the three
decrypted LSB must be different from the original LSB. In
this case: b’ i,j,k + bi,j,k = 1
On the other hand, if the embedded bit in the
pixel’s block is 0 and the pixel belongs to S0, or the
embedded bit is 1 and the pixel belongs to S1, the
decrypted LSB.
Data Extraction
The receiver has both the data hiding, he may aim
to extract the embedded data according to the data hiding
key. The values of M, Land S, the original LSB of the Np
selected encrypted pixels, and the (N-Np) * S/L - Np
additional bits can be extracted from the encrypted image
containing embedded data. By putting the Np LSB into
their original positions, the encrypted data of the Np
selected pixels are retrieved, and their original gray values
can be correctly decrypted using the encryption keys. In the
following, it will recover the original gray values of the
other (N-Np) pixels. Consider the case that the receiver has
the encryption key but does not know the data-hiding key.
Clearly, he cannot obtain the values of parameters and
cannot extract the embedded data. However, the original
image content can be roughly recovered.
III. PROPOSED SYSTEM
In our proposed technique we introduced the data hiding
technique on encrypted image using two keys such as
encryption key and data hiding key. First the sender and
receiver generates encryption key randomly using Diffie
Hellman key exchange algorithm. Sender encrypts the
cover image with the encryption key. Then generates data
hiding key randomly, then obtain the positions from the
ISSN: 2231-5381
data hiding. Before embedding the data bits we apply run
length encoding technique for compression of the image.
This algorithm uses arithmetic modulus as the
basis of its calculation. Suppose Alice and Bob follow this
key exchange procedure with Eve acting as a man in
middle interceptor (or the bad guy).Here are the calculation
steps followed in this algorithm that make sure that eve
never gets to know the final keys through which actual
encryption of data takes place.
 First, both Alice and Bob agree upon a prime number
and another number that has no factor in common.
Lets call the prime number as p and the other number
as g. Note that gis also known as the generator and p is
known as prime modulus.
 Now, since eve is sitting in between and listening to
this communication so eve also gets to know p and g.
 Now, the modulus arithmetic says that r = (g to the
power x) mod p. So r will always produce an integer
between 0 and p.
 The
first
trick
here
is
that
given x (with g and p known),it’s very easy to find r.
But given r(with g and p known) it’s difficult to
deduce x.
 One may argue that this is not that difficult to crack
but what if the value of p is a very huge prime
number? Well, if this is the case then
deducing x (if r is given) becomes almost next to
impossible as it would take thousands of years to crack
this even with supercomputers.
 This is also called the discrete logarithmic problem.
 Coming back to the communication, all the three Bob,
Alice and eve now know g and p.
 Now, Alice selects a random private number xa and
calculates (g to the power xa) mod p =ra. This
resultant ra is sent on the communication channel to
Bob. Intercepting in between, eve also comes to
know ra.
 Similarly Bob selects his own random private
number xb,
calculates
(g to
the
power xb)
mod p = rb and sends this rb to Alice through the same
communication channel. Obviously eve also comes to
know about rb.
 So eve now has information about g, p, ra and rb.
 Now comes the heart of this algorithm. Alice
calculates (rb to the power xa) mod p = Final
key which is equivalent to (g to the power (xa*xb) )
mod p .
 Similarly Bob calculates (ra to the power xb) mod
p = Final key which is again equivalent to (g to the
power(xb * xa)) mod p.
 So both Alice and Bob were able to calculate a
common Final key without sharing each other’s
private random number and eve sitting in between will
not be able to determine theFinal key as the private
numbers were never transferred.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 17 Number 1 – Nov 2014
Run Apply Encoding Algorithm:
IV. CONCLUSOIN
Suppose we are given a file or a source message
that has too many redundant characters. For example, an
average MS Word file has too many consecutive byte-255
and NULL characters. Is it possible to represent these
consecutive bytes or “runs” into a more compact form?
Indeed, a compression technique was designed to solve this
particular
problem.
It
is
called Run-Length
Encoding or RLE. Its name so accurately describes the
process because it encodes a run of bytes to the
following 2byte form:{byte,length},with length representing
the
number of runs of a single byte and which means that we
can encode as many as 255 consecutive runs.
Binary files. Another clever form of run-length encoding is to
encode if and only if there is a run. That is, do not encode an
additional byte for a single non-redundant byte: encode only
those redundant bytes. This is done by encoding twice the
byte and then encoding the length byte: {byte, byte, length}.
This way, we do not incur a length byte for those bytes which
occur only independently in a data stream. Thus, in the
decompression phase, the presence of a twin byte alerts us that
there is exactly a run of bytes. Hence, {‘b’, ‘b’, 8} means that
there are 10 runs of byte ‘b’. It follows that we must then
write the next eight bytes after the two. The previous example
would then be encoded like this:
{‘a’}, {‘b’, ‘b’, 8}, {‘e’}, {‘f’, ‘f’, 1}, {‘g’, ‘g’, 2},
{‘h’, ‘h’, 0}, {‘i’}, {j}, {‘k’}.
This encoding needs only 17 bytes for output. Notice that the
letters ‘a’ and ‘e’ are now encoded as is, with single bytes. For
very large files, this technique is more powerful than the
“byte-length” technique. This method can record at most 257
consecutive bytes (2 + (0..255)).
Another drawback we incur from this new technique,
however, is the additional symbol encoded. If there are only
two runs of a symbol, we would need an additional byte,
encoding the run with three bytes instead of just two bytes. In
general, however, this is more effective when we look at the
data as a single large file which may naturally have a series of
identical bytes.
This is a very simple compression method used for
sequential data. It is very useful in case of repetitive data. This
technique replaces sequences of identical symbols (pixels)
,called runs by shorter symbols. The run length code for a gray
scale image is represented by a sequence { Vi , Ri } where Vi
is the intensity of pixel and Ri refers to the number of
consecutive pixels with the intensity Vi as shown in the figure.
If both Vi and Ri are represented by one byte, this span of 12
pixels is coded using eight bytes yielding a compression ratio
of 1: 5.
After this after the data hiding we derive the
positions for embedding the data bits. At those positions we
replace the data bits in the encrypted cover image. From the
proposed technique we achieve more security over the
distortion and the data hiding. For the retrieving the data and
the image receiver have both keys encryption and data hiding
keys. Having any one of the key do not extract the message or
data.
ISSN: 2231-5381
The data of original image are entirelyencrypted by a stream
cipher. Although a data-hider does not know the original
content, hecan embed additional data into the encrypted image
by modifying a part of encrypted data.With an encrypted
image containing embedded data, a receiver may firstly
decrypt it usingthe encryption key, and the decrypted version
is similar to the original image. According to the data-hiding
key, with the aid of spatial correlation in natural image, the
embedded datacan be correctly extracted while the original
image can be perfectly recovered.
REFERENCES
[1] M. Johnson, P. Ishwar, V. M. Prabhakaran, D. Schonberg, and K.
Ramchandran,
“On
compressing
encrypted
data,”
IEEE
Trans.SignalProcess., vol. 52, no. 10, pp. 2992–3006, Oct. 2004.
[2] W. Liu, W. Zeng, L. Dong, and Q. Yao, “Efficient compression of
encryptedgray scale images,” IEEE Trans. Image Process., vol. 19, no.
4,pp. 1097–1102, Apr. 2010.
[3] X. Zhang, “Lossy compression and iterative reconstruction for
encryptedimage,” IEEE Trans. Inform. Forensics Security, vol. 6, no.
1,pp. 53–58, Feb. 2011.
[4] T. Bianchi, A. Piva, and M. Barni, “On the implementation of the
discreteFourier transform in the encrypted domain,” IEEE Trans.
Inform.Forensics Security, vol. 4, no. 1, pp. 86–97, Feb. 2009.
[5] T. Bianchi, A. Piva, and M. Barni, “Composite signal representation
forfast and storage-efficient processing of encrypted signals,” IEEE Trans.
Inform. Forensics Security, vol. 5, no. 1, pp. 180–187, Feb. 2010.
[6] N. Memon and P. W. Wong, “A buyer-seller watermarking
protocol,”IEEE Trans. Image Process., vol. 10, no. 4, pp. 643–649, Apr.
2001.
[7] M. Kuribayashi and H. Tanaka, “Fingerprinting protocol for
imagesbased on additive homomorphic property,” IEEE Trans.
ImageProcess., vol. 14, no. 12, pp. 2129–2139, Dec. 2005.
[8] M. Deng, T. Bianchi, A. Piva, and B. Preneel, “An efficient buyersellerwatermarking protocol based on composite signal representation,”
inProc. 11th ACM Workshop Multimedia and Security, 2009, pp. 9–18.
[9] S. Lian, Z. Liu, Z. Ren, and H. Wang, “Commutative encryption
andwatermarking in video compression,” IEEE Trans. Circuits Syst.
VideoTechnol., vol. 17, no. 6, pp. 774–778, Jun. 2007.
[10] M. Cancellaro, F. Battisti, M. Carli, G. Boato, F. G. B. Natale, andA.
Neri, “A commutative digital image watermarking and encryptionmethod
in the tree structured Haar transform domain,” Signal Processing:Image
Commun., vol. 26, no. 1, pp. 1–12, 2011.
BIOGRAPHIES
Vardhanapu Alekhya received B.tech degree
in Computer science &Engineering from
JNTU Kakinada University. She pursuing
M.tech (CSE) in Swarnandhra College of
Engineering & Technology (underthe
university of JNTU Kakinada.
Kaligithi Rajesh Kumar completed M.tech.
Currently he is working as Associate
Professor
in Swarnandhra College of
Engineering
and
Technology.(Under
University
of
JNTU
Kakinada).
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