International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014
A Pragmatic Approach in Lossless Data Hiding for JPEG
Images
T. S.Sandeep
1#
#1
, J. Shankar babu *2, Dr.N. Sudhakar Reddy@3
Assistant Professor, Dept of CSE,SVEW, TIRUPATI, AP, India
Associate Professor, Dept of CSE,SVEW,TIRUPATI, AP, India
3@
PRINCIPAL, SVCE, TIRUPATI, AP, India
2*
Abstract— In this paper Reversible Data hiding restores
the carrier once the removing hidden secret information.
Many reversible data hiding techniques were proposed
within the past few years, but on analysis, almost all does
not have in providing the security and authentication. This
paper proposes a novel reversible data hiding technique
which effort is separable, the receiver can extract the
initial image or additional embedded information or both
based on the keys hold from the receiver. Alternatively the
receiver can verify the information hided through the data
hider, so that the work proposes both security and
authentication. Digital steganography and watermarking
are both types of information hiding. Digital
watermarking usually mentioned as hiding for comforting
the data. Information hiding in image process could occur
the long term frame distortions and then the initial cover
medium is probably not prepared to be turned around
precisely, once the hidden knowledge are extracted out.
This work proposes a novel scheme for separable
reversible data hiding in encrypted images. Within the
first phase, a content owner encrypts the initial
uncompressed image having an encryption key. Then, a
data-hider may compress minimal significant bits of the
encrypted image by using a data-hiding step to produce a
sparse space to allow for some additional data. Through
an encrypted image containing additional data, if the
receiver gets the data-hiding key, he is able to extract the
additional data though he doesn't be aware of image
content. When the receiver contains the encryption key,
they can decrypt the received data to acquire an image
just like the original one, but cannot extract the additional
data.
Keywords: Reversible Data Hiding, Histogram, Stenography,
Performance, Watermarking.
I. INTRODUCTION
In an interactive buyer–seller protocol for invisible
watermarking, the seller does not know the exact watermarked
copy that the buyer receives. So the seller cannot create copies
of the original content containing the buyer’s watermark. If
ISSN: 2231-5381
the seller finds an unauthorized copy, the seller can identify
the buyer from the watermark using the unauthorized copy,
and hence the seller can prove this fact to a third party using a
dispute resolution protocol. In it is desired to transmit
redundant data over an insecure and bandwidth-constrained
channel, it is desired to first compress the data and then
encrypts it. Traditional techniques used to compress the data
first and then encrypt the data.
But we are reversing the order of these steps, thereby
first encrypting and then compressing the data. A significant
compression ratio can be achieved if compression is
Performed after encryption. Compression is performed by
standard source code and decryption by decompression.
Data hiding is referred to as a process to hide data
into cover media. This implies that the data hiding process
links two sets of data, a set of embedded data and another set
of cover media data. These two sets of data have different
applications. In covert communications, the hidden data may
often be irrelevant to the cover media. In authentication, the
embedded data is closely related to the cover media. In these
two types of applications, the invisibility of hidden data is an
important factor. In some cases of data hiding, the cover
media will experience some distortion due to data hiding and
cannot be inverted back to original media. That is, some
permanent distortion has occurred to the cover media even
after the hidden data have been extracted out. In other
applications, such as remote sensing and high-energy particle
physical experimental analysis, it is also desired that the
original cover media can be recovered because of the required
high-precision. In addition, information sharing was proposed
to protect the security of concerned data by transforming a
secret message into several shares which are then distributed
to a number of participants to keep. Such a secret sharing
scheme is useful for reducing the risk of incidental data loss
and advantageous for keeping a balance among the
participants: only when all the shares or a sufficient number of
them are collected from the participants can the secret
message be recovered correctly. This concept of secret sharing.
Conventionally, data hiding and information sharing are two
irrelevant issues in the domain of information security. In this
study, a new data hiding method based on the technique of
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International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014
information sharing is proposed for hiding data into PNG
(portable network graphics) images.
The reversible data hiding in encrypted image is
investigated, most of the work on reversible data hiding
focuses on the data embedding/extracting on the plain spatial
domain But, in some applications, an inferior assistant or a
channel administrator hopes to append some additional
message, such as the origin information, image notation or
authentication data, within the encrypted image though he
does not know the original image content. And it is also
hopeful that the original content should be recovered without
any error after image decryption and message extraction at
receiver side. The presents a practical scheme satisfying the
above-mentioned requirements and Fig. 1 gives the sketch. A
content owner encrypts the original image using an encryption
key, and a data-hider can embed additional data into the
encrypted image using a data-hiding key though he does not
know the original content. With an encrypted image
containing additional data, a receiver may first decrypt it
according to the encryption key, and then extract the
embedded data and recover the original image according to
the data-hiding key. In the scheme, the data extraction is not
separable from the content.
II. LITERATURE SURVEY
In the literature, many data hiding methods exploring the
spatial domain and Frequency domain of images has been
proposed. Bender et al. [12] proposed The technique of leastsignificant-bit (LSB) replacement, in which a secret message
is embedded in the least significant bits of image pixel values.
Mielikainen [13] Proposed a modified LSB replacement
method which embeds as many bits as the Conventional
method, but changes less pixel values. Yang et al. [14]
proposed an Adaptive k-LSB substitution method in which
larger values of k are adopted in the Edge areas of the cover
image and smaller ones are used for the smooth areas. Wang
et al. [15] transformed image block contents into coefficients
in the frequency domain By the discrete cosine transform
(DCT) and embedded secret bits by modifying the Magnitude
relations between the AC values of image blocks. Besides data
embedding Techniques using the DCT, the discrete wavelet
transform (DWT) [17] and the discrete Fourier transform
(DFT) [18-19] have also been used.
From another viewpoint, different types of images and files
can be used as cover Media for developing data hiding [2021]. In [21], Lee and Wu proposed a lossless Data hiding
method for palette-based images, which adjusts palette colors
and image Data to embed secret data and side information for
reconstruction of the original Image content. Lee and Tsai [9]
hid data into PDF files’ characters by using special ASCII
codes. Liu [10] made use of the change tracking function in
Microsoft Word to Hide data by a document degeneration
technique.
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In this paper, in addition to the aforementioned
spatial domain, frequency Domain and palettes of images for
use in data hiding, we try to explore a new Embeddable space
for data hiding, aiming at providing more data hiding
capacity, Better quality of the resulting stego-image and
stronger applicability. As a result, the PNG image with the
alpha channel plane is found to be capable of meeting these
Requirements mentioned previously. Specifically, in the
information-sharing-based Data hiding method proposed in
this study, a PNG image is used as the cover image in Which
the alpha-channel value of each pixel is set to be 255 initially.
In recent years, several researchers have revealed a
large form of image data hiding techniques in the literatures.
These techniques are often classified roughly into 3
approaches, i.e., the spatial domain, the frequency domain,
and also the compression domain. Within the spatial domain,
the cover image is altered directly and undetectably to hide the
secret message. Lee and Chen [18] proposed a steganographic
algorithm applied within the spatial domain during which the
smallest amount important bit (LSB) of every pixel within the
cover image was replaced by secret data. Later, Chang et al.
[19] found the best LSB substitution for embedding secret
data by using a dynamic programming strategy. By applying
each run-length coding and standard computation, Chang et al.
[20] designed 2 efficient data hiding ways for icon files and
grayscale files. The entire on top of ways is irreversible data
hiding schemes within the spatial domain. The reversible data
hiding scheme during this domain are often classified into 3
classes, i.e.
1) Data hiding by difference growth,
2) Data hiding by bar graph shifting, and
3) Data hiding by prediction error expansion.
In 2002, the primary distinction growth methodology
was planned [1, 2]. In 2012, Ni et al. planned the primary bar
graph shifting-based information concealment theme [3]. In
2007, Thodi and Rodriguez planned an information
concealment theme supported prediction error growth [4].
Supported the above 3 schemes, several data hiding ways [57] are planned to reinforce hiding capacity or cut back the
distortion of the stego-image. In the frequency domain, the
cover image should be preprocessed by separate cosine
transformation (DCT) [8], separate wavelet transformation
(DWT) [9], or separate Fourier remodel (DFT) [10] to induce
frequency coefficients. Once the frequency coefficients are
changed slightly to embed the secret information, the stego
image is often obtained by inversing the changed frequency
coefficients. In 2001, Fridrich et al. proposed an invertible
data hiding theme to change the quantization table by
employing a second-order operate. In 2002, chang et al.
embedded the secret data into the mid-frequency coefficients.
Next, Xuan et al utilized a reversible scheme to engraft
information into the high-frequency DWT coefficients with
bar graph modification.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014
In 2007, Chang Jiang et al.presented a lossless
embedding theme for JPEG pictures. In the compression
domain, the secret data are embedded by the alteration of the
compression code. Through the compression methodology,
the scale of the digital image information is often reduced
considerably. Actually, we have a tendency to transmit digital
image data within the compression format in our standard of
living. Many researchers have interest in hiding data within
the compression domain. Among compression Techniques,
like JPEG, JPEG2000, VQ, and block truncation coding
(BTC), VQ is a simple and efficient methodology that's wide
used. Chang Jiang et al. proposed a reversible, data hiding
algorithmic program based on the SMVQ. Within the same
year, Yang et al. planned AN MFCVQ based, reversible
watermarking theme by using four adjacent blocks to code the
present block. However, the visual quality and hiding
capability of yang et al.’s scheme weren't sensible enough. In
2009, Chang Jiang et al. used the conception of joint
neighboring coding (JNC) within the VQ index table for
embedding secrets with changeability. During this paper, a
completely unique information hiding scheme based on the
VQ codebook is explored. The proposed method uses a
codebook that has been resorted by PCA (principle component
analysis) and exploits the gap of two codeword’s, which are
just like one image block, to embed the secret information. In
keeping with the key to be embedded and also the difference
between those 2 codeword’s, the initial image block is
reworked into a difference variety table that's compressed by
entropy coding before causing to the receiver. At the receiver
finish, once cryptography the compressed code, the key
information are often extracted, and also the image are often
recovered as a VQ compressed image.
III. PROPOSED METHODOLOGY
The proposed scheme uses AES encoding
algorithmic program that uses an equivalent keys for each
encoding and decryption. AES is AN iterated block cipher
with a set block size of 128 and a variable key length. AES
uses variable variety of rounds that are fastened. The key
growth algorithmic program is based on the assumption of a
128 bit key. AES calls for a bigger variety of rounds once we
use a key length aside from 128 bits. The key expansion
algorithmic program should obviously generate an extended
schedule for the 12 rounds needed by a 192 bit key and also
the fourteen rounds needed by a 256 bit keys. If a change in
one bit of the encoding key happens it'll have an effect on the
spherical key for many rounds. The key expansion algorithm
ensures that AES has no weak keys throughout every round;
following operations are performed on every state
1.
2.
3.
Sub Bytes: each byte within the state is replaced by
another one, using the S-Box.
Shift Row: each row within the 4x4 array is shifted a
particular quantity to the left.
Mix Column: a linear transformation on the columns
of the state.
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4.
Add round Key: each byte of the state is combined
with a byte key.
3.1 THE SUBSTITUTE BYTES STEP
This is a computer memory unit-by-byte substitution
and also the substitution byte for every input byte is found by
using the lookup table. The scale of the lookup table is 16 ×
16. To seek out the substitute byte for a given input byte, we
have a tendency to divide the input byte into 2 4-bit patterns,
every yielding A whole number price between 0 and 15. We
are able to represent these whole number values by their hex
values zero through F. is one amongst the hex values
employed as a row index and also the alternative as a column
index for reaching into the 16×16 lookup table. The entries
within the lookup table are constructed by a mix of GF (28)
arithmetic and bit mangling. The goal of the substitution step
is to reduce the correlation between input bits and output bits
at the byte level. The bit mangling a part of the substitution
step ensures that the substitution can't be described within the
variety of evaluating a simple mathematical function. We
have a tendency to initial fill every cell of the sixteen ×
sixteen table with the byte obtained by joining along its row
index and also the column index. we next replace the worth in
every cell by its multiplicative inverse in GF (28) supported
the irreducible polynomial x8+x4+x3+x+1. The value 00 is
replaced by itself since this component has no inverse. Let’s
represent a byte stored in each cell of the table by
b7b6b5b4b3b2b1b0 wherever b7 is that the msb and b0 the
LSB. Therefore, the bit pattern stored 9 cells with row index
nine and column index 9 is 10001010, showing that b7 is 1
and b0 is 0.
This byte-by-byte substitution step is reversed throughout
decryption. The 16×16 lookup table for decryption is
constructed by beginning get into an equivalent manner as for
the encryption lookup table.
3.2 THE SHIFT ROW STEP
The Shift Row transformation consists of
1.
2.
3.
4.
Not shifting the primary row of the state array at any
condition.
Circularly shifting the second row by one byte to the
left side.
Circularly shifting the third row by two bytes to the
left side.
Circularly shifting the last row by three bytes to the
left facet.
The input block is written in column-wise manner. That’s the
primary four bytes of the input block fill the primary column
of the state array and also the next four bytes the second
column then on. For secret writing, the encoding steps are
shifted in only the other fashion. At the start the primary row
is left unchanged. The second row is shifted to right by one
byte and also the third row to right by 2 bytes and also the last
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International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014
row to right by 3 bytes. All shifts performed are circular
manner.
3.3 MIX COLUMN STEP
This step replaces every byte of a column by a function of all
the bytes within the same column. additional exactly, every
byte in an exceedingly column is replaced by twice that byte,
and three times successive byte, and the byte that comes next,
and the byte that follows. The words ‘next’ and ‘follow’
discuss with bytes within the same column, and there that
means is circular, within the sense that the byte that's next to
the one within the last row is that the one within the initial
row. This stage called round Column is largely a substitution
however it makes use of arithmetic of GF (28). Every column
is operated individually. Every byte of every column is
mapped into a brand new value that's a function of all four
bytes within the column.
3.4 ADD ROUND KEY TRANSFORMATION
This stage called AddRoundKey uses the 128 bits of
state and is bitwise XORed with the 128 bits of the round key.
This operation is performed in column wise manner. This
transformation is as easy as possible which helps in efficiency
but it affects every bit of state.
3.5 IMAGE ENCRYPTION
Assume an original image is within uncompressed
format and every pixel with gray value falling directly into
[0, 255] is presented by 8 bits.
Ba,b,c= ba,b,cΦ ra,b,c
where ra,b,c are determined by an encryption key by
using a standard stream cipher. Then, Ba,b,c are concatenated
orderly since the encrypted data. Various of secure stream
cipher methods might be used here to make sure which
anyone without the encryption key, say for example a
potential attacker or even the data hider, cannot acquire any
information regarding unique content through the encrypted
data.
3.6 DATA EMBEDDING
Within the data embedding phase, some parameters
are embedded right into a small number attached with
encrypted pixels, and furthermore the particular LSB with the
other encrypted pixels are compressed to generate a space for
accommodating a further data along with the original data at
the positions occupied through the parameters. The detailed
procedure can be as follows In accordance with a data-hiding
key, the data-hider pseudo-randomly selects Np encrypted
pixels that may be utilized to hold the parameters for data
hiding.
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Here, Np is really a small positive integer, for instance,
Np=20. The other (N-Np) encrypted pixels are pseudorandomly permuted and divided into a variety of groups, each
and every of which contains L pixels.
The permutation way is usually dependant on the data-hiding
key.
For every pixel-group, gather the M the very least
considerable items of the L pixels, as well as denote them as B
(k,1) , B (k,2) …… B(k,M*L) in which k can be a group
index within [1,(N-Np)/L] and M is generally a positive
integer less than 5. The data-hider also generates a matrix G
sized (M*L – S) * M*L, that is consists of two parts.
The left part will be the identity matrix as well equally the
suitable part is pseudo-random binary matrix produced from
the data-hiding key.
For each and every group , which can be product with all the
G matrix to create a matrix of size (M * L-S). That includes a
sparse bits involving size S, when the information is
embedded as well as organize the pixels in to the original
form and repermutated to create a original image.
3.7 DATA EXTRACTION
When the particular receiver has both data-hiding, he might
make an effort to extract the embedded data Based on the
data-hiding key, the values of M,L and S, the original LSB
from the Np chosen encrypted pixels, as well as the (N-Np) *
S/L - Np further bits might be extracted in the encrypted
image containing embedded data. By putting the particular
Np LSB within their original positions, the encrypted data
with the Np determined pixels are retrieved, and their
particular original gray values might be correctly decrypted
while using the encryption keys. Within the following, we are
going to recover the initial gray values with the other (N-Np)
pixels.
This specific paper proposes a new novel scheme for
separable reversible data hiding in encrypted image. Within
the proposed scheme, the initial image is encrypted having an
encryption key as well as the additional data are embedded in
the encrypted image by using a data-hiding key. Through an
encrypted image containing additional data, in the result the
receiver only has the data-hiding key, he is able to acquire the
extra data though he doesn't are aware of the image content. In
case he's got just the encryption key, he is able to decrypt the
received data to have an image exactly like the original one,
but cannot extract the embedded additional data. In the event
the receiver has both the data-hiding key and also the
encryption key, they can extract the additional data and
recover the initial image without the error if the amount of
additional data will be not too big.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 7 Number 1- Jan 2014
IV. CONCLUSION
In this particular paper, a new scheme intended for separable
reversible data hiding in encrypted image is proposed, which
often includes image encryption, data embedding as well as
data-extraction/image recovery phases. Within the first phase,
this content owner encrypts the initial uncompressed image
having an encryption key. Although a data-hider will not
really know the dimensions as well as original written content,
they may compress the smallest amount involving significant
bits of the encrypted image employing a data-hiding step to
make a new sparse space to accommodate the additional data.
By having an encrypted image containing additional data, the
receiver may extract a further data only making use of the
data-hiding key, or get the image just like the original one
only using the encryption key. Once the receiver has each of
the keys, they can extract the additional data and recover the
original content without any error by exploiting the spatial
connection in normal image within the event the quantity of
more data is not too big. When the lossless compression
technique is useful for the encrypted image containing
embedded data, the additional data may be still extracted as
well as the original content can as well be recovered
considering that the lossless data compression will not affect
the content with the encrypted image containing embedded
data. However, the lossy compression method in suitable for
encrypted images produced by pixel replacement just isn't
suitable here considering that the encryption is performed by
bit-XOR operation. Later on, a comprehensive combined
image encryption and data hiding suitable for lossy
compression should get further study
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