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Proceedings ArticleDOI

A highly secure video steganography using Hamming code (7, 4)

02 May 2014-pp 1-6
TL;DR: A secure video steganography algorithm based on the principle of linear block code that has high embedding efficiency and the system's quality is close to the original video quality.
Abstract: Due to the high speed of internet and advances in technology, people are becoming more worried about information being hacked by attackers. Recently, many algorithms of steganography and data hiding have been proposed. Steganography is a process of embedding the secret information inside the host medium (text, audio, image and video). Concurrently, many of the powerful steganographic analysis software programs have been provided to unauthorized users to retrieve the valuable secret information that was embedded in the carrier files. Some steganography algorithms can be easily detected by steganalytical detectors because of the lack of security and embedding efficiency. In this paper, we propose a secure video steganography algorithm based on the principle of linear block code. Nine uncompressed video sequences are used as cover data and a binary image logo as a secret message. The pixels' positions of both cover videos and a secret message are randomly reordered by using a private key to improve the system's security. Then the secret message is encoded by applying Hamming code (7, 4) before the embedding process to make the message even more secure. The result of the encoded message will be added to random generated values by using XOR function. After these steps that make the message secure enough, it will be ready to be embedded into the cover video frames. In addition, the embedding area in each frame is randomly selected and it will be different from other frames to improve the steganography scheme's robustness. Furthermore, the algorithm has high embedding efficiency as demonstrated by the experimental results that we have obtained. Regarding the system's quality, the Pick Signal to Noise Ratio (PSNR) of stego videos are above 51 dB, which is close to the original video quality. The embedding payload is also acceptable, where in each video frame we can embed 16 Kbits and it can go up to 90 Kbits without noticeable degrading of the stego video's quality.

Summary (1 min read)

Introduction

  • Technology, people are becoming more worried about information being hacked by attackers.
  • The security of the steganography scheme is depending directly on the embedding efficiency [4].
  • Motion vectors with large size are selected for embedding the secret message.
  • The direction of macro blocks depends on the motion vectors’ components.
  • First the video stream is separated into frames and each frame’s color space is converted to YCbCr.

A. Linear block codes

  • In the standard array, there are no two equal vectors at the same row.
  • Two cosets either overlap or intersect completely or not at all.

B. Hamming codes (7, 4)

  • The Hamming code is one of the most well-known block code methods that can do both error detection and correction on a block of data.
  • In the Hamming code technique, the original information will be coded by adding some extra data with the minimum amount of redundancy, which is called the codeword, of length n bits [10].
  • Otherwise, any change in the message during transmission will lead to flipping one or more bits of the message; then it needs an error correction process.
  • The first assumption R=1111111 is received without any errors.

C. Data embedding phase

  • Data embedding is a process of hiding a secret message inside host videos, and it can be done by the following steps: 1- Convert the video stream into frames.
  • 8- Reposition all pixels of YUV components to the original frame pixel position.
  • Those keys are shared between sender and receiver in both data embedding and extracting processes.
  • The first key is used to reposition pixels in Y, U, V, and the secret message into a random position, which makes the data chaotic.
  • The XOR function that has been used increases the quality of the system.

D. Data extracting phase

  • Data extracting is a process of retrieving the secret message from the stego videos which can be done by the following steps: 1- Convert the video stream into frames.
  • The third part of the figure shows the hidden message before and after embedding.
  • In Table I, the average PSNR for all video sequences is shown for each Y, U, and V component and all are greater than 51dB.
  • This algorithm is considered a high embedding efficiency algorithm due to the low modification on the host data that makes the stego videos have a very good quality.
  • In addition to the three keys that the authors have used, they also encode and decode the message before and after embedding, which improves the security of their scheme to be even better.

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©2014 IEEE. Reprinted, with permission, from R.J..
Mstafa, and K.M. Elleithy, "
A Highly Secure Video
Steganography using Hamming Code (7, 4)." In
Proceedings of Systems, Applications and Technology
Conference (LISAT), Farmingdale, NY, 2014. DOI:
10.1109/LISAT.2014.6845191.
This material is posted here with permission of the IEEE.
Such permission of the IEEE does not in any way imply
IEEE endorsement of any of the University of
Bridgeport's products or services. Internal or personal use
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Abstract Due to the high speed of internet and advances in
technology, people are becoming more worried about
information being hacked by attackers. Recently, many
algorithms of steganography and data hiding have been
proposed. Steganography is a process of embedding the secret
information inside the host medium (text, audio, image and
video). Concurrently, many of the powerful steganographic
analysis software programs have been provided to unauthorized
users to retrieve the valuable secret information that was
embedded in the carrier files. Some steganography algorithms
can be easily detected by steganalytical detectors because of the
lack of security and embedding efficiency.
In this paper, we propose a secure video steganography
algorithm based on the principle of linear block code. Nine
uncompressed video sequences are used as cover data and a
binary image logo as a secret message. The pixels positions of
both cover videos and a secret message are randomly reordered
by using a private key to improve the system’s security. Then the
secret message is encoded by applying Hamming code (7, 4)
before the embedding process to make the message even more
secure. The result of the encoded message will be added to
random generated values by using XOR function. After these
steps that make the message secure enough, it will be ready to be
embedded into the cover video frames. In addition, the
embedding area in each frame is randomly selected and it will be
different from other frames to improve the steganography
scheme’s robustness. Furthermore, the algorithm has high
embedding efficiency as demonstrated by the experimental
results that we have obtained. Regarding the system’s quality, the
Pick Signal to Noise Ratio (PSNR) of stego videos are above 51
dB, which is close to the original video quality. The embedding
payload is also acceptable, where in each video frame we can
embed 16 Kbits and it can go up to 90 Kbits without noticeable
degrading of the stego video’s quality.
Keywords
__
Video Steganography, Hamming Code, Linear
Block Code, Security, Embedding Efficiency, Embedding
Payload.
I. INTRODUCTION
NTERNET makes people’s lives much easier than before;
they can use it to pay their bills, buy their goods, exchange
important messages between parties at far distances, and
many other things. Without protecting that valuable
information, attackers can obtain them in different ways.
Steganography is one of the methods that protects and hides
valuable data from unauthorized people and even without
them having any suspicion of the data’s existence. Human
Visual System (HVS) can’t recognize a slight change that
happens in the media cover such as audio, image and video
[1].
There are two important factors that every successful
steganography system should take into consideration, which
are embedding efficiency and embedding payload. First, the
steganography scheme that has a high embedding efficiency
means good quality of stego data and less amount of host
(carrier) data are going to be changed [2]. Any obvious
distortion to the viewers will increase the probability of the
attacker's suspicion and the secret information can be easily
detected by some of the steganalysis tools [3]. These kinds of
schemes are difficult to be detected by the steganalytical
detectors. The security of the steganography scheme is
depending directly on the embedding efficiency [4].Second,
the high embedding payload means the capacity of secret
information to be hidden inside host data is large. To be more
specific, the two factors embedding efficiency and embedding
payload have a type of contradiction. Increasing efficiency
will cause the capacity of embedding to have a low payload.
Changing the balance between these two factors mainly
depends on the users and the type of steganography scheme
[2].
The rest of the paper is organized as follows. Section 2
presents some of the previous work. Section 3 introduces an
overview of the Linear Block Code and Hamming code, and
then presents our Steganography scheme. Section 4 we discuss
experimental results and analyze them. Section 5 provides the
conclusions.
II. RELATED WORK
In 2009, Eltahir et al presented a video steganography
based on the Least Significant Bit (LSB). Authors tried to
increase the size of the secret message into the video frames.
They analyzed video into frames then each frame was used as
a still image. A 3-3-2 approach has been used which means
taking the LSB of all RGB color components (3-bits of Red,
3-bits of Green, and 2-bits of Blue). The reason for taking 2-
bits of blue color is because the HVS is more sensitive to the
A Highly Secure Video Steganography using
Hamming Code (7, 4)
Ramadhan
J. Mstafa and Khaled M. Elleithy, Senior Member, IEEE
Department of Computer Science and Engineering
University of Bridgeport
Bridgeport, CT 06604, USA
rmstafa@bridgeport.edu
I

blue color than the other two colors. The results demonstrated
that the hidden message can take one third of overall video
size. This is considered an improvement of the LSB algorithm
[5].
In 2010, Feng et al proposed a novel of video
steganography scheme based on motion vectors as carriers to
embed the secret message in H.264 video compression
processing. The algorithm also uses the principle of linear
block codes to reduce motion vectors modification rate. The
algorithm has a good quality of stego data, which is proved by
the low modification rate of motion vectors. The PSNRs that
were obtained in both flower and foreman videos are more
than 37 dB [6].
In 2011, Hao et al proposed a novel video steganography
method based on a motion vector by using matrix encoding. A
motion vector component that has high amplitude among both
horizontal and vertical components is chosen to embed the
secret message. The Human Visual System can see the change
that occurs when the object is moving slowly, while if the
same object moves quickly the HVS won’t be able to feel the
change that happens. Motion vectors with large size are
selected for embedding the secret message. The macro blocks
that are moving quickly will generate motion vectors with
large amplitude. The direction of macro blocks depends on the
motion vectors components. For example, if the vertical
component is equal to zero that means the macro block
direction is moving vertically. The quality of the tested videos
that was obtained is more than 36 dB [7].
In 2012, Rongyue et al proposed an efficient BCH coding
for steganography which is embedding the secret information
inside a block of cover data by changing some coefficients.
Authors have improved the computational time of the system
and the complexity becomes low because of the system’s
linearity [8].
In 2013, Liu et al proposed a robust data hiding scheme in
H.264 compressed video stream, where they have prevented a
drift of intra-frame distortion. To give the system more
robustness, authors have encoded the message using BCH
code before making the embedding process. The host data is
the DCT coefficients of the luminance I-frame component.
The obtained results have a high quality and robustness [9].
III. THE PROPOSED STEGANOGRAPHY SCHEME
Our algorithm uses an uncompressed video stream which
is based on the frames as still images. First the video stream is
separated into frames and each frame’s color space is
converted to YCbCr. The reason for using YCbCr color space
is that it removes correlation between Red, Green, and Blue
colors. A luminance (Y) part is brightness data, which the
human eyes are more sensitive to than the color parts. As a
result, the color parts (chrominance) can be subsampled in the
video stream and some information will be discarded.
A. Linear block codes
A block code is a linear block code if a summation of
two codewords is also a codeword, and the binary linear
block code is applied to bits of blocks. An (n, k) binary
linear block code has 2
k
columns and 2
n-k
rows in a linear
code array. Where k is refers to k-dimensional subspace
and n refers to n-dimensional vector space.
V
n
= {(C
0
, C
1
, …, C
n-1
)|C
j
ϵ GF(2)} where n is the
length of the code and k is a number of symbols. In the
standard array, there are no two equal vectors at the same
row. Assume C is a (n, k) code on Galois Field GF (2),
then:
All X vectors of length n belong to a coset of C.
Each coset has 2
k
vectors.
Two cosets either overlap or intersect completely
or not at all.
If C+Y is a coset of C and X as belong to (C+Y),
then C+X=C+Y.
B. Hamming codes (7, 4)
The Hamming code is one of the most well-known block
code methods that can do both error detection and correction
on a block of data. In the Hamming code technique, the
original information will be coded by adding some extra data
with the minimum amount of redundancy, which is called the
codeword, of length n bits [10]. The added part consists of
parity information of length (n-k) bits where k is the length of
message that is expected to be coded [2]. In this paper, the (7,
4) Hamming code is used that can detect and correct a single
bit error of data or parity. First, the message (m
1
, m
2
, m
3
, m
4
)
of length k bits (k=4) is encoded by adding three parity bits
(p
1
, p
2
, p
3
) to become the codeword of length n (n=7), which is
ready for transmission. There are different ways to mix both
types of data (message and parity) together and the general
combination is to put the parity bits at position 2
i
such as (p
1
,
p
2
, m
1
, p
3
, m
2
, m
3
, m
4
) where i=0, 1, ... ,(n-k-1).
The Hamming codes are linear codes so they have two
matrices: parity-check matrix H and generator matrix G,
which they need for both encoding and decoding. On the
encoding side, each message M, which consists of 4-bits, will
be multiplied by the generator matrix and then have modulo of
2 applied; the result is the codeword X of 7-bits ready to be
sent through a noisy channel.
Where




On the decoding side, for the purpose of checking the
encoded message of 7-bits R (data + parity) will be received,
then will be multiplied by the transpose of the parity-check
matrix, and taking modulo of 2 again.

, where







The result is a syndrome vector Z (z
1
, z
2
, z
3
) of three bits,
which has to be all zeroes (000) if it’s an error-free message.
Otherwise, any change in the message during transmission
will lead to flipping one or more bits of the message; then it
needs an error correction process.
Example: Assume we have a message M
1
of 4-bits (1, 1, 1, 1)
and the Hamming code (7, 4) is done by the following steps:
1- Calculate
, the result is (3, 3, 3, 1, 1, 1,
1) then taking modulo of 2, the result is the codeword
X=1111111, which is sent through the
communication channel.
2- At the destination, to get the correct message the
syndrome vector Z must be zero. The first
assumption R=1111111 is received without any
errors. Then Z will become (0, 0, 0), where
.
3- In the second assumption, suppose that during
transmission due to the noisy channel one of the bits
has changed. The received data will be R=1111011,
then calculating the syndrome we will get Z=433, and
taking modulo of 2 the syndrome will become
Z=011.
4- Comparing Z value with the parity-check matrix H, it
appears that the Z value (0, 1, 1) is equal to the 5
th
row (0, 1, 1) of the H matrix, which means that the 5
th
bit of R has changed.
5- Correcting the 5
th
bit of R by flipping it to 1, R then
is corrected to become (1, 1, 1, 1, 1, 1, 1).
6- The four first bits are the original message M
1
(1, 1,
1, 1) and the last three other bits will be ignored.
C. Data embedding phase
Data embedding is a process of hiding a secret message
inside host videos, and it can be done by the following steps:
1- Convert the video stream into frames.
2- Separate each frame into Y, U and V components.
3- Change the position of all pixels in three components
Y, U and V by a special key.
4- Convert the message (which is a binary image) to a
one dimension array, and then change the position of
the whole message by a key.
5- Encode each 4 bits of the message using Hamming
(7, 4) encoder.
6- The result of the encoded data, which consists of 7
bits (4 bits of message + 3 bits of parity) is XORed
with the 7 bits of random value using a key.
7- Embed the result of those 7 bits in one pixel of YUV
components (3-bits in Y, 2-bits in U and 2-bits in V).
8- Reposition all pixels of YUV components to the
original frame pixel position.
9- Rebuild the video stream again from those embedded
frames.
There are three keys that have been used in this work,
which give to our steganography scheme an improvement in
both security and robustness. Those keys are shared between
sender and receiver in both data embedding and extracting
processes. The first key is used to reposition pixels in Y, U, V,
and the secret message into a random position, which makes
the data chaotic. In order to select the locations for embedding
the secret message into the host data, the second and third
keys are used. They are used to pick the random rows and
columns respectively in each chaotic Y, U and V component.
The XOR function that has been used increases the quality of
the system. The block diagrams of the data embedding phase
and the data extracting phase are illustrated in Figure 1 and
Figure 2 respectively.
Figure 1: Block diagram for data embedding phase.

D. Data extracting phase
Data extracting is a process of retrieving the secret
message from the stego videos which can be done by the
following steps:
1- Convert the video stream into frames.
2- Separate each frame into Y, U and V components.
3- Change the position of all pixel values in the three Y,
U, and V components by the special key that was
used in the embedding process.
4- Obtain the encoded data from the YUV components
and XOR with the random number using the same
key that was used in the sender side.
5- Decode 4 bits of the message by the Hamming
decoder.
6- Reposition the whole message again into the original
order.
7- Convert the message array to 2-D.
Figure 2: Block diagram for data extracting phase.
IV. EXPERIMENTAL RESULTS AND ANALYSIS
In this paper, a database of nine standard Common
Interchange Format (CIF) video sequences is used, with the
size (288 X 352) and the format 4:2:0 YUV. All video
sequences are equal in length with 300 frames in each one.
The secret message is a binary image logo for the University
of Bridgeport (UB) with a size of 128 X 128 pixels. The
MATLAB software program is used to implement this work
and test our experiment results.
In Figure 3, an example of one frame (frame no. 111) in
the Foreman video is chosen. The first part of the figure shows
that the three components of the 111
th
frame are separated.
Then it shows some locations that have been chosen randomly
for the secret message. The embedded locations are different
in each component inside one frame and they differ from one
frame to next, which mainly depends on the private key. The
second part of the figure shows frame no. 111 before and after
the embedding process. The last part of the figure shows the
whole message that has been embedded and extracted 100%
correctly.
Figure 3: A sample result of frame number 111 for the Foreman video. a)
Shows the selected areas for embedding in YUV components for frame
number 111. b) Shows the 111
th
frame both the original and the stego frames.
c) Shows the embedded and extracted message.

Citations
More filters
Journal ArticleDOI
TL;DR: Experimental results demonstrate that the proposed method achieves higher embedding capacity as well as better visual quality of stego videos and the two preprocessing steps increase the security and robustness of the proposed algorithm as compared to state-of-the-art methods.
Abstract: Due to the significant growth of video data over the Internet, video steganography has become a popular choice. The effectiveness of any steganographic algorithm depends on the embedding efficiency, embedding payload, and robustness against attackers. The lack of the preprocessing stage, less security, and low quality of stego videos are the major issues of many existing steganographic methods. The preprocessing stage includes the procedure of manipulating both secret data and cover videos prior to the embedding stage. In this paper, we address these problems by proposing a novel video steganographic method based on Kanade-Lucas-Tomasi (KLT) tracking using Hamming codes (15, 11). The proposed method consists of four main stages: a) the secret message is preprocessed using Hamming codes (15, 11), producing an encoded message, b) face detection and tracking are performed on the cover videos, determining the region of interest (ROI), defined as facial regions, c) the encoded secret message is embedded using an adaptive LSB substitution method in the ROIs of video frames. In each facial pixel 1 LSB, 2 LSBs, 3 LSBs, and 4 LSBs are utilized to embed 3, 6, 9, and 12 bits of the secret message, respectively, and d) the process of extracting the secret message from the RGB color components of the facial regions of stego video is executed. Experimental results demonstrate that the proposed method achieves higher embedding capacity as well as better visual quality of stego videos. Furthermore, the two preprocessing steps increase the security and robustness of the proposed algorithm as compared to state-of-the-art methods.

91 citations


Cites background from "A highly secure video steganography..."

  • ...The number of parity bits that must be added to the message is p=n−k with the rate of r=k/n [7, 26]....

    [...]

Journal ArticleDOI
TL;DR: The performance assessment for video Steganography and the future popular video steganography including H.265 video stegansography, robust video steGANography and reversible video steaganography are introduced.

81 citations

Journal ArticleDOI
TL;DR: Experimental results and analysis validate the effectiveness of the proposed framework in terms of security, image quality, and computational complexity and verify its applicability in remote patient monitoring centers.
Abstract: In this paper, the problem of outsourcing the selective encryption of a medical image to cloud by resource-constrained devices such as smart phone is addressed, without revealing the cover image to cloud using steganography. In the proposed framework, the region of interest of the medical image is first detected using a visual saliency model. The detected important data is then embedded in a host image, producing a stego image which is outsourced to cloud for encryption. The cloud which has powerful resources, encrypts the image and sent back the encrypted marked image to the client. The client can then extract the selectively encrypted region of interest and can combine it with the region of non-interest to form a selectively encrypted image, which can be sent to medical specialists and healthcare centers. Experimental results and analysis validate the effectiveness of the proposed framework in terms of security, image quality, and computational complexity and verify its applicability in remote patient monitoring centers.

61 citations

Proceedings ArticleDOI
15 Apr 2015
TL;DR: A high embedding payload of video steganography algorithm has been proposed based on the BCH coding to improve the security of the algorithm and is compared to both the Least Significant Bit (LSB) and [1] algorithms.
Abstract: Video steganography has become a popular topic due to the significant growth of video data over the Internet. The performance of any steganography algorithm depends on two factors: embedding efficiency and embedding payload. In this paper, a high embedding payload of video steganography algorithm has been proposed based on the BCH coding. To improve the security of the algorithm, a secret message is first encoded by BCH(n, k, t) coding. Then, it is embedded into the discrete wavelet transform (DWT) coefficients of video frames. As the DWT middle and high frequency regions are considered to be less sensitive data, the secret message is embedded only into the middle and high frequency DWT coefficients. The proposed algorithm is tested under two types of videos that contain slow and fast motion objects. The results of the proposed algorithm are compared to both the Least Significant Bit (LSB) and [1] algorithms. The results demonstrate better performance for the proposed algorithm than for the others. The hiding ratio of the proposed algorithm is approximately 28%, which is evaluated as a high embedding payload with a minimal tradeoff of visual quality. The robustness of the proposed algorithm was tested under various attacks. The results were consistent.

56 citations

Journal ArticleDOI
TL;DR: Experimental results validate the performance of the proposed cryptosystem in terms of robustness and high-level security compared to other recent image encryption schemes during dissemination of important keyframes to healthcare centers and gastroenterologists for personalized WCE.

54 citations

References
More filters
Proceedings ArticleDOI
03 Aug 2008
TL;DR: A novel steganographic scheme based on the (7, 4) Hamming code for digital images that achieves a double embedding payload and a slightly lower visual quality of stego images compared with the related works is proposed.
Abstract: High payload information hiding schemes with the good visual quality of stego images are suitable for steganographic applications such as online content distribution systems. This paper proposes a novel steganographic scheme based on the (7, 4) Hamming code for digital images.The proposed scheme embeds a segment of seven secret bits into a group of seven cover pixels at a time. The experimental results show that the proposed scheme achieves a double embedding payload and a slightly lower visual quality of stego images compared with the related works.

64 citations


"A highly secure video steganography..." refers background in this paper

  • ...First, the steganography scheme that has a high embedding efficiency means good quality of stego data and less amount of host (carrier) data are going to be changed [2]....

    [...]

  • ...The added part consists of parity information of length (n-k) bits where k is the length of message that is expected to be coded [2]....

    [...]

  • ...Changing the balance between these two factors mainly depends on the users and the type of steganography scheme [2]....

    [...]

Proceedings ArticleDOI
03 Apr 2009
TL;DR: How the Least Significant Bit insertion (LSB) method is used on video images or frames, in addition to the usage of the human vision system to increase the size of the data embedded in digital video streaming.
Abstract: Steganography is the idea of hiding private or sensitive data or information within something that appears to be nothing out of the ordinary.In this paper we will overview the use of data hiding techniques in digital video as still images. We will describe how we can use the Least Significant Bit insertion (LSB) method on video images or frames, in addition to the usage of the human vision system to increase the size of the data embedded in digital video streaming.

45 citations

Journal ArticleDOI
TL;DR: The BCH syndrome coding for steganography is now viable ascribed to the reduced complexity and its simplicity of the proposed embedder.
Abstract: This paper presents an improved data hiding technique based on BCH (n,k,t ) coding. The proposed embedder hides data into a block of input data by modifying some coefficients in the block in order to null the syndrome. The proposed embedder can hide data with less computational time and less storage capacity compared to the existing methods. The complexity of the proposed method is linear while that of other methods are exponential for any block size n. Thus, it is easy to extend this method to a large n. The BCH syndrome coding for steganography is now viable ascribed to the reduced complexity and its simplicity of the proposed embedder.

45 citations


"A highly secure video steganography..." refers background in this paper

  • ...Authors have improved the computational time of the system and the complexity becomes low because of the system's linearity [8]....

    [...]

Journal ArticleDOI
TL;DR: This paper presents a robust readable data hiding algorithm for H.264/AVC video streams without intra-frame distortion drift, and can get more robustness, effectively avert intra- frame distortion drift and get high visual quality.

41 citations


"A highly secure video steganography..." refers background in this paper

  • ...The obtained results have a high quality and robustness [9]....

    [...]

Journal ArticleDOI
TL;DR: A key contribution of this paper is to compute log likelihood ratios for RA decoding, taking into account the many-to-one mapping between the host coefficients and an encoded bit, for ME, to address the problem of robustness to attacks.
Abstract: In matrix embedding (ME)-based steganography, the host coefficients are minimally perturbed such that the transmitted bits fall in a coset of a linear code, with the syndrome conveying the hidden bits. The corresponding embedding distortion and vulnerability to steganalysis are significantly less than that of conventional quantization index modulation (QIM)-based hiding. However, ME is less robust to attacks, with a single host bit error leading to multiple decoding errors for the hidden bits. In this paper, we employ the ME-RA scheme, a combination of ME-based hiding with powerful repeat accumulate (RA) codes for error correction, to address this problem. A key contribution of this paper is to compute log likelihood ratios for RA decoding, taking into account the many-to-one mapping between the host coefficients and an encoded bit, for ME. To reduce detectability, we hide in randomized blocks, as in the recently proposed Yet Another Steganographic Scheme (YASS), replacing the QIM-based embedding in YASS by the proposed ME-RA scheme. We also show that the embedding performance can be improved by employing punctured RA codes. Through experiments based on a couple of thousand images, we show that for the same embedded data rate and a moderate attack level, the proposed ME-based method results in a lower detection rate than that obtained for QIM-based YASS.

39 citations


"A highly secure video steganography..." refers methods in this paper

  • ...In the Hamming code technique, the original information will be coded by adding some extra data with the minimum amount of redundancy, which is called the codeword, of length n bits [10]....

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Frequently Asked Questions (1)
Q1. What are the contributions in this paper?

Concurrently, many of the powerful steganographic analysis software programs have been provided to unauthorized users to retrieve the valuable secret information that was embedded in the carrier files. In this paper, the authors propose a secure video steganography algorithm based on the principle of linear block code. Furthermore, the algorithm has high embedding efficiency as demonstrated by the experimental results that the authors have obtained. The embedding payload is also acceptable, where in each video frame the authors can embed 16 Kbits and it can go up to 90 Kbits without noticeable degrading of the stego video ’ s quality.