1
Data Embedding in Scrambled Digital Video for Data Security &
Authentication
Jamna Kaur1 , Rachna Rajput2
1
M.Tech Student of Guru Kashi University, Talwandi Sabo, jamnaparmarg7@gmail.com
2 Assistant Prof. Guru Kashi University, Talwandi Sabo, Rachnacse12@gmail.com
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Abstract: As technology advances, multimedia applications
increase exponentially in day-to-day life. Multimedia
applications such as video telephony, video conferencing, TV,
streaming video/audio online, and many other applications are
in demand in video industry. Many different video codec
standards such as H.261, MPEG-1, MPEG-2, H.263, and H.264
are implemented. The work of this is to first briefly describe
about encoding and decoding process, and then it discusses
more details about different modules of encoder and decoder,
and the related algorithms. In this work video is encoded into
different frames, and convert into images where the encoded
key is hidden that the private key and security is provided by
private key. When the decoding is performed then the encoded
frame with private key is automatically selected. Also calculate
the Parameter of video. The Dissertation is completed
successfully by hiding Digital video data.
Keyword: Discrete Cosine Transform, PSNR, MSE, LSB(Least
Significant bit).
I.
INTRODUCTION
In various multimedia technologies, security and privacy has
become an important. The main goal of cryptography is
keeping data secure form unauthorized attackers. Therefore
data is encrypted through process of Encryption. Data
cryptography mainly is the scrambling of the content of data,
such as text, image, audio, video and so forth to make the
data unreadable, invisible or unintelligible during
transmission or storage called Encryption. The reverse of
data encryption is data Decryption, which recuperate the
original data. The reverse of data encryption is data
decryption with digital video transmission, encryption
technologies are needed that can protect digital video from
attacks during transmission. Due to the huge size of digital
videos, they are usually transmitted in compressed formats
such as MPEG.
A . Need of Video Encryption
Requirements of Video Encryption Nowadays there are
many traditional cryptography systems that provide
powerfully security encryption methods. However, most of
them are not appropriate for video since the amount of video
data is much greater than text, for which the traditional
cryptography systems were originally designed. The
performance of video encryption methods must be evaluated
from four requirements like security, complexity,
compression overhead and format compliance.For
preventing unwanted viewing of transmitted video, for
example from law enforcement video surveillance being
relayed back to a central viewing centre. To protect the
private multimedia messages that is exchanged over the
wireless or wired networks. Video Encryption is helpful in
securing videos used in services like video on demand
(VOD), Video conferencing- learning.
B. Data Hiding Techniques (LSB)
The least significant bit (in other words, the 8th bit) of some
or all of the bytes inside an image is changed to a bit of the
secret message. Digital images are mainly of two types
(i) 24 bit images.
(ii) 8 bit images.
In 24 bit images we can embed three bits of information in
each pixel, one in each LSB position of the three eight bit
values. Increasing or decreasing the value by changing the
LSB does not change the appearance of the image. so the
resultant image looks almost same as the cover image. In 8
bit images, one bit of information can be hidden. The
advantages of LSB techniques are: Popularity, Easy to understand and
comprehend, High perceptual transparency, Low degradation in the
image quality. However, there are few weaknesses of using LSB. It is
very sensitive to any kind of filtering or manipulation of the image
.Scaling, rotation, cropping, addition of noise, or lossy compression to the
stego-image will destroy the message. On the other hand, for the hiding
capacity, the size of information to be hidden relatively depends to the
size of the cover- image.
II.
PARAMETERS USED
A. PSNR (Peak Signal-to-Noise Ratio): A high quality
image has small value of Peak Signal to Noise Ratio (PSNR)
or PSNR is defined as the ratio of signal power to noise
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power. It basically obtains the gray value difference between
resulting image and original image. PSNR is most
commonly used to measure the quality of reconstruction of
lossy compression code (for image compression). The signal
in this case is the original data, and the noise is the error
introduced by compression.
PSNR is defined as follow:
Start
Read the input video
Dividing the video into
frame
B. MSE (Mean Square Error): MSE is the sum over all
squared value differences divided by image size and by
three.
Calculate the Frame separation and
Convert Frame to image file.
n=size (Input Image);
M=n(1);
N=n(2);
MSE
=
sum(sum((Input
ImageReconstructed
Image).^2))/(M*N);
C. Proposed Algorithm
Step 1: Start the program.
Step 2: Reads the video and stores it as a image files in a
folder
Step 3: Calculate the Frame separation and Convert Frame
to image file.
Step 4: Write image file.
Step 5: Apply Encoding on the frames of the video. Apply
the LSB technique encoding the video stream after the
frame separation.
Step 6: Generate the Hexadecimal key for security.
Step 7: Apply decoded frame to check for authentication
and validation
Step 8: Apply the decoding process on video
Step 9: PSNR and MSE values and decoded time.
Step 10: Stop.
Apply the encoding frame and Apply the LSB
technique encoding the video stream
Generate the Security key
Apply decoding on frame to check for
authentication and validation
Apply the decoding
process on video
Then Calculate the Parameter.
PSNR and MSE values and
decoded time.
Figure 2: The basic working of the system.
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RESULT & ANALYSIS
Their are different figures that shows how the video is
processed and how the system tools works in MATLAB.In
this we upload the digiat video.
III.
Figure 3.4: Frame selection of input video
We select a frame frome number of frame .After this
Encoding is performed frame.
Figure 3.1: First input video that is used to hide the data
Figure 3.2: Second input video that is used to hide the data.
In this we select the input video and perform frame sepration
into 8
8 block .After frame separation number of frames
are made .
Figure 3.5: Encoding the selected frame
When encoding is perform on frame then we encode the
video frame by frame.In this Private Key for video security
we Generate. By pressing the button Key and this Key is
embeded with the encoded frame.
Figure 3.3: Browsing the Input video .
Figure 3:6: Value of Private Key
Private Key = 405fdb1a05093b98
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encoded key is hidden that the private key. When the
decoding is performed then the encoded frame with private
key is automatically selected and gives the original frame of
the input video that is shown in above snap shorts.
In this we calculate decoding time of digital video and also
the PSNR and MSE of the digital video after the data
scrambling.
Video Name
Decoding
Time
PSNR
MSE
matchvideo.mp4
3.920764
sec
22.2859
384.1368
Pacific
Ocean.mp4
14.142753
sec
20.2996
606.9017
Illusion
video.mp4
3.833233
sec
5.6684e+03
10.5962
Figure 3.7: Decoded the frame
In this after Private Key Generation.We decoded the frame.
Result Table: Table of Decoding Time, PSNR and MSE
value.
IV.
Figure 3.8: Decode the video frame by frame.
After this validation is performed .if validation is accurate
then calculate the parameter of video.
Figure 3.9:Calculate the Decoding Time, PSNR and MSE
value.
In this research work video is encoded into different frames,
after encoding the frame is converted into images where the
LITERATURE SURVEY
There are many algorithms in existence for scrambling of
the video frames and to encrypt them. The proposed scheme
treats the video as a framing sequence. Secondly an index
number is provided for each frame. Then the frames are
encrypted to hide the information using thresholding
method. Proper keys are used to scramble the frames of the
video initially. The content of the frames remains the same.
The Grouping Of Pictures (GOP) provides a feature of
categorizing the frames and pictures of same size under a
particular group.[ref 1].
The watermark embedding is processed in the DCTD. To
achieve high performance, the proposed system architecture
employs pipeline structure and uses parallelism. This system
based watermarking system features low power
consumption, low cost implementation, high processing
speed, and reliability. In this study we should concentrate on
applying the watermarking algorithm to other modern video
compression standards, such as MPEG-4/H.264.[ref.2].In
This we focuses on the various methods for video
Encryption. Fro analysis of Amongst the all different
different approaches. According the analysis of Pure
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Permutation Algorithm , Zig-Zag Permutation Algorithm,
Chaos Based Encryption Algorithms, Deformation &
formation Algorithms, Video Encryption algorithm
(VEA).This analysis selective encryption takes less time as
compared to full encryption. Zigzag method & chaos based
method are hot research topics for encryption of video but
takes more time. Therefore a encryption algorithm based on
I-frames & xor has been defined.[ref.3].This technique that
uses watermark nesting and encryption. Nesting means it
embeds an extra watermark into the main watermark and
then embeds the main watermark into the cover image. For
encryption XOR operation is used. For embedding
watermarked in Cover Image by DWT based technique. By
using watermark nesting we can embed more number of bits
in the cover image as compare to without watermark nesting.
Due to nesting feature we can embed some metadata about
watermark also. This technique uses encryption, so it
increases the security of watermarks. For instance if
watermarking key is hacked still the attacker will not be able
to identify the watermark because it is encrypted. [ref.5]
V. CONCLUSION
The work in this dissertation in terms of the various
parameters that have been considered while scrambling the
digital video for security.The fact that the proposed method
embeds the data directly in the spatial domain (pixel values)
makes it immune to some very common errors, which appear
in other competitive data hiding techniques working in the
compressed domain. In conclusion, the main advantages of
the proposed method are its low complexity and the
possibility of using the compressed stream for hiding
different data many times, without first decoding and then
re-encoding the video sequence. This makes the method
appropriate for real-time applications. Future work might
involve a real time implementation of the system so that the
maximum number of videos is enhanced with the help of
different filters. In the future work DWT is implemented
with hard and soft threshold for data scrambling in digital
videos authentications and security.
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