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International Conference on Explorations and Innovations in Engineering & Technology (ICEIET – 2016)
Adaptive Steganalysis of Least Significant Bit
in wrl images Ms.Mohana Priya.S Ms.Bindiya.S
UG Scholar, Department of Information Technology, UG Scholar, Department of Information Technology, SNS College of Engineering, SNS College of Engineering,
Coimbatore, India Coimbatore, India [email protected] [email protected]
Ms. Aruna.A
Assistant Professor, Department of Information Technology, SNS College of Engineering,
Coimbatore, India [email protected]
ABSTRACT
Steganography is the art of covert communication. A stenographic system thus embeds
hidden content in unremarkable cover media. In earlier systems, reversible data hiding algorithm is
used. The drawbacks behind this algorithm are the
hiding rate (1.536 bpp) often causes more distortion in the image content and low degradation in the image
quality. This system was proposed to improve the
security and robustness done in 3D images. Initially, the 3D image is viewed and the secret message is
embedded into the 3D image. The secret message is hidden in the 3D image using the key file. After the
embedding process, the 3D image is sent to the
receiver. The receiver receives the secret key and extracts the message embedded in the 3D image. The
secret data or secret message is viewed by the receiver.
If the secret key entered by the receiver is wrong then only the 3D image is shown to the receiver. The
accuracy rate used in this system is 97.6%. Here, the
3D model which is based on least significant bit algorithm to protect the embedded information. This
algorithm can be widely used for digital protection and other aspects of identity hidden.
Keywords – Least significant bit algorithm; 3D
images; digital watermarking; data confidentiality;
Hidden data; Secret key; Data extraction.
I INTRODUCTION
Data hiding technique aims to embed some secret information into a carrier signal by altering the
insignificant components for copyright protection or
covert communication. During the past years, a
steganography technique has received more attention.
Steganography is the art and science of invisible communication, which attempts to conceal the existence
of hidden messages. The steganalysis, on the other
hand, aims to discover the hidden data from the cover medium.In the recent years, 2D and 3D images are the
most popular digital media for carrying secret messages. JPEG format for 2D images and VRML
format for 3D images are the most popular image
formats for image storage and exchange on the Internet at this time, many information hiding methods and/or
tools implement hiding message in 3D images.
With the development of science and technology,
three dimensional models have been used in many fields, such as medical industries, movies, video games,
constructions and so on. With the growth of application
areas, more and more digital products of three-dimensional model spread on the network. The
copyright protection of three-dimensional model has become increasingly important. Study on the three
dimensional model for digital watermarking technology
is becoming a new field of digital watermarking research [1]. Like the two-dimensional image
watermarking, digital watermarking algorithm for three-
dimensional model began from the spatial algorithm.
In 2014, X.Feng proposed two different
algorithms to embed watermark into the three-dimensional model [5], but the watermark information
is not encrypted. Once the watermarking algorithm is
cracked, the watermark information is not safe. In the same year, Wang put forward a digital watermarking
algorithm for three-dimensional model which is based on the structural feature of the vertex distribution [6]:
the algorithm has the drawbacks that the amount of data
embedded is limited. In general cases, the data-hiding operation will result in distortion in the host signal.
However, such distortion, no matter how small it is, is
unacceptable to some applications, e.g., military or medical images.
In this case it is imperative to embed the additional
secret message with a reversible manner so that the original contents can be perfectly restored after
extraction of the hidden data. A number of reversible
data hiding techniques have been proposed, and they can be roughly classified into three types: lossless
compression based methods, difference expansion (DE)
methods, and histogram modification (HM) methods. The lossless compression based methods make use of
statistical redundancy of the hos t media by performing lossless compression in order to create a spare space to
accommodate additional secret data. Thereby, this paper
applies encrypted holographic watermarking algorithm to the three-dimensional model to protect the watermark
information (such as copyright information with
specific identity) and improve the security, capacity of watermark embedding. We can get the original
watermark information from the encrypted watermark
only by the decrypt template and check the information of specific authentication. The proposed algorithm has
high security and good robustness to common attacks.
II EXISTING SYSTEM
EMBEDDING ALGORITHMS
The flow chart of watermark embedding algorithm is shown in Figure 1.The steps are as follows:
1) Process the three-dimensional model with an affine
invariant; 2) Sort i of vertices in ascending order, and store the corresponding r in the matrix j D with sizen n
, then keep the location information of i in a mark
matrix. j is a positive integer and satisfies j ( ) 1 N the empty in the last matrix can be filled with zero; 3)
Generate random matrix a and matrix b as double random phase modulation, which is key to encryption
and decryption of holographic watermark; 4) The
watermark image (such as copyright information)
modulated by the random phase a takes Fourier
transform, then the transformed image is modulated by the random phase b and takes inverse Fourier transform;
5) Coaxial holographic watermark H is then constructed
by double random phase encryption; 6) Three-dimensional Models is reconstructed by matrix. 8)
Spherical coordinates (r, θ, φ) is converted into
Euclidean coordinates (x, y, z), and the formula of
computation.(11) The hologram algorithm is used
successfully in the 3D model watermarking.
EXTRACTION ALGORITHMS
The flow chart of watermark extraction algorithm is shown in Figure 2.The steps are as follows:
1) Relocate [9] and Resample operator [10]; 2) Affine
invariant processing of three-dimensional model; 3) Move the barycentre of the model to the coordinate
origin and Euclidean coordinates (x, y, z) is converted into spherical coordinates (r, θ, φ); 4) Sort i of vertices
in ascending order, and find a matrix with size n
according to the location of i in mark matrix. If we cannot find the full matrix, then choose the matrix
which is relatively integrate and the missing part can be
filled with zeros.
In this way, hologram watermarking matrix 'h is reconstructed (With multiple watermarking
embedded, the relatively integrity one is enough); 5) Coaxial holographic watermark H is given 6) the
holographic watermark H takes Fourier transform. And
the transformed information is modulated by the random phase –b and takes inverse Fourier transform.
Then it is modulated by the random phase -a. And we
get the watermark image.
III PROPOSED SYSTEM
Steganography, the art of covert communication. It hides the presence of a message. It can imperceptibly
embed data into a cover object. Traces of data embedding can be found within the characteristics of
the stegano objects.The dissemination such as using the
(VRML) to represent 3D graphics on the Web.3D models have become potential covers for covert
communication. Data Hiding is the art of hiding the fact
that communication is taking place, by hiding information in other information.VRML File formats
can be used(.wrl). 3D images are the most popular because of their frequency on the Internet. Data is
encrypted domain preserves the confidentiality of the
content. LSBs of the elements pointed by the determined locations are used for embedding and
extraction. Embedded watermark data and Spread-
spectrum based watermarking technique is proposed. It
avoids data degradation due to traditional watermarking.
ALGORITHM:
The procedure of the proposed algorithm is illustrated
in Fig. 1. Given that totally pairs of histogram bins are to be split for data embedding, the embedding
procedure includes the following steps: 1) Pre-process:
The pixels in the range of and are processed as mentioned in SectionII-C excluding the first 16 pixels in
the bottom row. A location map is generated to record
the locations of those pixels and compressed by the JBIG2 standard [11] to reduce its length. 2) The image
histogram is calculated without counting the first 16
pixels in the bottom row. 3) Embedding: The two peaks (i.e. the highest two bins) in the histogram are split for
data embedding by applying Eq. (1) to every pixel counted in the histogram. Then the two peaks in the
modified histogram are chosen to be split, and soon
until pairs are split. The bit stream of the compressed location map is embedded before the message bits
(binary values).The value of, the length of the
compressed location map, the LSBs collected from the 16 excluded pixels, and the previous peak values are
embedded with the last two peaks to be split. 4) The lastly split peak values are used to replace the LSBs of
the 16 excluded pixels to form the marked image.
The extraction and recovery process include the
following steps: 1) The LSBs of the 16 excluded pixels are retrieved so that the values of the last two split
peaks are known. 2) The data embedded with the last
two split peaks are extracted by using Eq. (2) so that the value of, the length of the compressed location map, the
original LSBs of 16 excluded pixels, and the previously split peak values are known. Then the recovery
operations are carried out by processing all pixels
except the 16 excluded ones with Eq.(3).The process of extraction and recovery is repeated until all of the split
peaks are restored and the data embedded with them are
extracted. 3) The compressed location map is obtained from the extracted binary values and decompressed to
the original size. 4) With the decompressed map, those
pixels modified in pre-process are identified.
Among them, a pixel value is subtracted by if it is less than 128, or increased by otherwise. To comply
with this rule, the maximum value of is 64 to avoid ambiguity. At last, the original image is recovered by
writing back the original LSBs of 16 excluded pixels.
SYSTEM ARCHITECTURE:
MODULES:
• Viewing 3D-image module
• Data hiding module
• Network process module
• Data extracting module
VIEWING 3D-IMAGE MODULE
In this Module only we are going to view the 3d objects. A steganographic method called adjacent bin
mapping (ABM) is presented. Firstly, it is applied to 3D
geometries by mapping the coordinates within two adjacent bins for data embedding. When applied to
digital images, it becomes a kind of LSB hiding, namely
the algorithm. In order to prevent the detection using a metric named histogram tail, the hiding is performed in
a pseudorandom order.
DATA HIDING MODULE
We are going to apply Robust Watermark Embedded scheme is used in it.After apply the watermark
technique the data will hided.The hided data we will
send through network and generate one secret key for every data. Finally the watermarked data and the key
will send to destination through network.
NETWORK PROCESS MODULE
Then upload the two files we give the data which we are
going to hide in the three dimensional file. Then we will do the parity check by taking the last bit. Here, the LSB
algorithm is used.
DATA EXTRACTING MODULE
In this module we are going to retrieve the hided data from the 3d model. This process will be done by given
the saved 3d file in hiding module. After checking the
source file it wIll retrieve the content from the given file. A robust watermarking algorithm is proposed to
embed watermark into compressed and encrypted.
IV EXPECTED RESULTS
The expected results of the proposed system are the
measured in terms of efficiency and performance rate. The proposed work has the efficiency rate of 97.6%.The
performance rate will be high when compared to the existing system. The secret message sent in the 3D
images will be maintained with high security. The
message sent through 3D images will achieve high confidentiality. The encryption and decryption done in
the proposed system will be quite easy when compared
to the existing system.
V CONCLUSION
In this paper we have presented a new strong watermarking for 3D model. This new method is based
on Least significant bit algorithm, using double random phase modulation to make the embedding watermark
information more secure. The results will clearly show
that the presented watermarking procedure can tag objects with watermarks in a strong way. It is invisible
and the cropping attacks can be successfully handled.
Also the algorithm guarantees the good performance of the watermark robustness to attacks such as noise
addition; model simplification and affine attacks.The 3D images can be rotated and prevented from all the
attacks.
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