I.
Introduction
The
well-known of the Internet and WWW has changed the method digital data is
handled. Data hiding deals with the facility of embedding data into a digital
cover with a minimum amount of perceivable squalor, i.e., the embedded data is
hidden or low to a human observer. Data hiding consists of two sets of data,
specifically the cover medium and the embedding data, which is called the
message. Transform domain is generally preferred for hiding data since, for the
equal strength as for the spatial domain; the result is more satisfying to the
Human Visual System (HVS).
We seek to
embed much larger volumes of data than required for hiding inside the video,
targeting applications such as steganography and seamless upgrade of
communication and storage systems, rather than digital privileges management.
Second, because of our target applications, we aim for strength not against
malicious attacks such as Stir mark’s geometric attacks, but against “natural”
attacks, such as compression (e.g., a digital image with secret content may be
compressed as it change hands or as it goes over a low bandwidth link in a
wireless network). Uncompressed video data has been utilized by the majority of
the video data hiding methods. A big quantity change domain data hiding in
MPEG-2 videos is proposed by Sarkar et al. [2].
Cryptology is procedure of converting plain
text to cipher text and vice versa.
Cryptology deals with usage different variety of cryptosystems to
encrypt and decrypt the data with the use of a key. Private key cryptographic
technique is one in which the same key is used to encrypt and decrypt the
message Cryptography and key replace techniques are well described in [3-6].
Steganography, future from
the Greek words stegos, meaning cover and graphia which means writing, is the
art and knowledge of hiding the fact that communication is taking place.
Steganography and cryptography are strongly related. Cryptography scramble
messages so they cannot be understand. Steganography on the other hand, will
hide the message so there is no information of the existence of the message in
the original place .In some situations, sending an
encrypted message will arouse misgiving while an invisible message will not do
so [7].
II.
related work
Nithin n,
AnunKumar M Bongle G. P. Hegde in [8] have planned Image Encryption based on
FEAL algorithm. Quick Encryption Algorithm an encryption/decryption
policy for gray scale images is proposed. The FEAL is also called block cipher
Encryption algorithm. FEAL works nearly like Data Encryption Standard (DES)
algorithm, but it is quicker than DES. The proposed image encryption algorithm
is estimation based on histogram learning and key indifference analysis and
results obtained are satisfactory. This algorithm has one big drawback;
Encryption technique should be not secure enough even if there is little
alteration in secret key real image outline is produced after 80% key matching.
Abirand Ali in [9] has proposed a novel chaos-based algorithm
for image encryption. at first image pixel points are shuffled using 2D chaotic
map. The originality of the image encryption lies in the integration of chaotic
substitution technique based on DNA coding and the harmonizing rule. To
calculate the security of the proposed method authors have conducted
relationship test, information entropy study, histogram study, and key
sensitivity analysis and difference analysis between original and encrypted
image. This method concludes with effect that “chaotic DNA exchange method
enhances the numerical properties of the encrypted image”.
Xin Zhanga, Weibin Chenn [10] have proposed a latest Chaotic Algorithm for Image Encryption. The chaos-based image cryptosystem typically
consists of two stages [2]. The pure image is given at its input. There are
various stages in the chaos based image cryptosystem. [a]misunderstanding and
[b] diffusion. The confusion period is the pixel permutation where the point of
the pixels is scrambled over the complete image without disturbing the
significance of the pixels and the image becomes unrecognizable. The chaotic
behavior is controlled by the early condition and control parameters which are
resulting from the 16-character key.In second stage of the encryption Process
we are going to change the value of each and every pixel in the whole image an
most important device to protect image from attackers. This method has a big
disadvantage image size and pixel ratio is increased evaluate than FEAL
Algorithm.
Steganography are
being paid more import day by day. Though steganography is a extremely old
method of embedding information behind some object, but still this is very
efficient for secure data move and data exchange. Today this method is used for
digital objects like text, audio, video and images [15]. Some technician
develop Secret image is first
encrypted by using BLOWFISH algorithm which has extremely good recital and is a
most controlling technique compared to other Algorithms type of algorithm (ex
AES, DES, RSA) [16]. The video segmentation is a technique of detecting
changing frames in video and one of the essential techniques required for able
management of video data [17] several video segmentation algorithms have been
proposed[18].
III.
proposed methodology
The
implementation stage involves secure planning, implementation, investigation of
the existing system and it’s constraints on implementation, scheming of methods
to achieve exchange and estimate of changeover methods. For more security
provided by steganography techniques.
The main aim of the proposed system is to send text
message and file behind a video which is imperceptible for human being eye. Here the system is proposed for
high authority, robust and Information Hiding the in DCT (Discrete Cosine
Transform) domain. A latest encoding method called Class Dependent Coding
Scheme (CDCS) is used to raise the embedding capacity, which can communicate
the same information using fewer number of bits [11]. High imperceptibility is
achieved by selecting well-organized DCT blocks for Embedding data using energy
thresholding scheme. On analysis, of a digitized video before and after a
message was inserted [11], will show video files that appeared to have no
extensive visual differences. The DCT is used to embed the box file, which
casts embedded data into the chosen region in the DCT domain [12]. Embed the
file in the selected section gives increase to invisibility.
Text
Processing two processes,
encryption and decryption together form the cryptographic process. For ensuring
security, the Data are encrypted by the sender before transmitting them and are
decrypted by the receiver after receiving them so that only the sender and the
future person can see the satisfied in the image. Blowfish algorithm which uses
a key of variable size up to 448 bits. Blowfish symmetric block cipher algorithm encrypts block data of
64-bits at a time
A.
Blowfish Algorithm
Blowfish algorithm uses a
Feistel network for data encryption which iterates the purpose 16 times. Each
about include a key needy permutation and data dependent changeover. Process of
data encryption and the different steps in encryption are described below as
Split the 64
bit block into two equivalent blocks having 32 bits size each (XL and XR).
The left block
XL is XOR’d with primary constituent of P-block, and thus obtained result is
fed to the F function. 1 P
In the F
function block, substitution operation is carried out where the given 32 bit
input is transformed into another 32 bit output.
The output
from F block is XOR’d with right half XR and the results obtained are swapped
as shown in the Figure.1
After
completing each round successfully, the so formed right half become the new
left half or vice versa.
These steps
are continued up to 16 rounds.
The last left and right halves are not swapped
but XOR’d with seventeenth and eighteenth P box elements.
So obtain
effect is the cipher text which is non comprehensible to outsiders and
attackers
Figure.1 blowfish flow
B. Class Dependent Coding
Schema
Three different
non extend beyond special classes.
Class
A (most frequently appearing character
set in secret message),
Class B
(Average frequently appearing) and
Class C
(Less frequently appearing characters).
Only capital letters, alphanumeric and few
special characters will further reduce the number of bits. Needed to represent
each character in each class. Encoding
technique based on Huffman encoding schema. We have designed variable length
code to represent each class A message “telemedicine” needs only of 61 numbers
of bits with CDCS as compared to 84 bits with ASCII. Here we have saved 23 bits
(27.38 % saving). This saving can further be increase with increase in message
length as well as increase in number of redundancy. The CDCS scheme is not only
saving the number of bits per character but also provides security.
m = ( N1+2 N2+2 N3
)+4h (1)
where,
h= N1+ N2+ N3 (2)
Table I . If N1, N2 and N3 are the whole
number of characters belong to Class A, Class
B and Class C respectively, Total number of bits to be embedded is given by
below table
This bit alignment saving can more be
increase in message length as well as increase in amount of redundancy. The
CDCS scheme is not only saving the quantity of bits per character but also
provides protection [20].
Class
|
Class code
|
Length
|
A
|
1
|
1-bit
|
B
|
00
|
2-bit
|
C
|
01
|
3-bit
|
Table I.
Table I Class data size variation
B.
Discrete Cosine Transform
DCT is like a encoder
and decoder. The first stage of image compression is DCT [11] encoder. It
consists of FDCT, quantize, and entropy encoder. The second stage is DCT
decoder [13][14]. It consists of entropy decoder, debutanizer and inverse
mapped.
·
The input image is N by M
·
f(i,j) is the strength of the pixel in row i and
column j;
·
F(u, v)
is the DCT coefficient row k1 and column k2 of the DCT.
·
For most images, much of the indication power
lies at less frequencies;
these appear in the higher left corner
of the DCT.

(1)
For
u,v = 0,1,2,3,….7

(2)
For
x,y = 0,1,2,3,….7
·
Compression is achieved since the lesser right
values represent upper frequencies, and are often small - small enough to be
neglected with small visible distortion
·
The DCT input is an 8 by 8 array of integers.
This array contain pixel's gray scale
level;
8 bit
pixels have levels from 0 to 255.
(i) Steps Required dispatcher
·
Select Real input video file uncompressed format
·
Extract video frames select frames (Images) by
frames (images) automatically to hide find the free space on the image pixel
using DCT
·
To encrypt the secured data of file using
blowfish algorithm with secured Key Value.
·
Automatically embedding the selected (encrypted
cipher text) to detected free space on selected frame
·
This embedding steps using DCT and CDCS
technique, DCT using embedding event and CDCS used to increase data length and
data security.
·
Finally getting secured Steganography video file
that video definitely viewable format. shown in the Figure.2
Figure.2 Dispatcher Side Process Flow to Create Steno
Video
(ii) Steps Required
Recipient
·
Receive the stegno video file.
·
Select
the Stegno video file.
·
Enter
the Secure Key value for before retrieving information
·
Extract
all frames and select Stegno frames
·
frames
one by one from Stegno video file
·
To
divide the real video file and secure data from Stegno video file .shown
in the Figure.3
·
Then
save or read the real secure data
·
End
Fig ure.3 Recipient Side
Process Flow to retrieve secure information from Stego video
IV EXPERIMENTAL
RESULTS
This Current system workings on
uncompressed grayscale video, but as the video is uncompressed file volume is
more this puts limitation on memory. This system is not lossless and reversible
as embedding data in frame results in a stable distortion of the original frame
or concealed data but within suitable range. This technique video or frame are
not loss this real shape or streaming after embedding secure data in video
file.
Related results are here getting some
video into an single frame only:
Result 1:
Embedding Process
The above frame is selected real video
(single frame) that uncompressed video frame. After developed an embedding
event with use of DCT, CDCS and Blowfish algorithm with secret key value
embedding event done for selected video file. shown in the Figure.4
Fig ure.4 Original image
uncompressed image
.
Embedding Event = Video
+(Secret information + Secret Key)
Example: Video=film.3gp Secure-information=hello
Secret
key=lakka123 Output=stegnofilm.3gp
Result 1:
Retrieving Process
After Embedding event done after transfer
video file for Recipient.Recipient is selecting the Stegno-video and extract
frame (to select single Frame foe ex below frame) that is compressed Video
frame, but not changing for viewable format at same time that frame have a
encrypted secret data inside the frame.When recipient put the secret key then
the user got real information from the select video. After retrieving the
information at time also that video viewable.
Retrieving Event=Stegno video-(Encrypted Message-secure key) Real data=stegnofilm.3gp-(Secret encrypted
data-lakka123) Real data =hello
That same time data file
also embedding and retrieving in video file in same procedure. shown in
the Figure.5
Figure.5 Stegno image compressed image
This Proposed Technique
embedding user secure information or data hidden into the video file use of
secure key value. When recipient trying to retrieving secure information
embedding video file put the 100% real secure key then only recipient get full
secure data otherwise got an Error message and just use Stego video or Segno
frame for is fully viewable.
Result 2:The Result 1 Procedure followed same lifecycle another video
file and another selected frame. Original image
uncompressed image as shown in the Figure.6
Figure.6 Original image uncompressed image
Segno image compressed
image as shown in the Figure.7
Figure.7 Segno image
compressed image
This technique using an
three main method that is like a DCT (Discrete Cosine Transform), CDCS (Class
Dependent Coding Schemes) and blowfish algorithm.
V. CONCLUSION
AND FUTURE WORK
The proposed methodology is a Information
Hiding technique for provides high Information Hiding strength and robustness
against the attacks such as compression and tampering. The benefit of the
future method is that the embedded message could still be extract after common
image processing attacks like compression done at video level and tampering
done at frame level. This development simulation results almost similar to the
thesis analysis. In future this thesis can be enhanced in the way to generate
key for automatically using user data(Ex ,name ,DOB) In this key used to AES
algorithm do an encryption and decryption process , And also support on 3gp and avi video formats future develop on other
video formats like mp4, mkv etc. Further this work can be improved by making
the feature available for multiple video formats.
IV.
Acknowledgment
The authors would like to thank the CS department and anonymous reviewers and
associate editor for their comments that greatly improved the manuscript
V.
References
[1].S. K. Kapotas, E. E.
Varsaki, and A. N. Skodras, “Data hiding in H- 264 encoded video sequences,” in
Proc. IEEE 9th Workshop Multimedia
Signal Process., Oct. 2007, pp. 373–376.
[2].A. Sarkar, U. Madhow, S.
Chandrasekaran, and B. S. Manjunath, “Adaptive MPEG-2 video data hiding
scheme,” in Proc. 9th SPIE Security
Stegno graphy Watermarking Multimedia Contents, 2007, pp. 373–376.
[3].D. Luciano and Gordon
Prichett. Cryptology: From Caesar
Ciphers to Public-Key Cryptosystems. The College Mathematics Journal, vol. 18, No. 1, pp. 2-17,
January 1987.
[4]. S. T. F. Al-Janabi and M.
A. Rasheed. Public-Key Cryptography
Enabled Kerberos Authentication. In
Proc. Of IEEE conference on Developments in E-systems Engineering, pp.
209-214, Dec. 6-8, 2011.
[5].G.P. Biswas. Diffie–Hellman technique: extended to
multiple two-party keys and one multi-party key. Published in IET Information Security, vol. 2, No. 1, pp. 12–
18, 2008.
[6]. R. Sharma. A Novel Approach to combine Public-key encryption with Symmetric-key
encryption. The International
Journal of Computer Science & Applications, Vol. 1, No. 4, pp. 8-15,
June 2012.
[7]. J.R. Krenn, Steganography and Steganalysis, 2004.
[8].Nithin N,
Anupkumar M Bongale G. P. Hegde Image Encryption based on FEAL algorithm, 2013
[9] A. Awad and A. Miri. A
New Image Encryption Algorithm Based on a Chaotic DNA Substitution Method. In
Proc. Of IEEE international conference on communication, pp. 1011-1015, 2012.
[10] Xin Zhang, Weibin Chen,
“A New Chaotic Algorithm For Image Encryption”, pp 889-892 IEEE ICALIP2008.
[12]. S. H. Kamali, M. Hedayati, R. Shakerian and M.
Rahmani. A New Modified Version of
Advanced Encryption Standard Based Algorithm for Image Encryption. In Proc. of International Conference on
Electronics and Information Engineering, vol 1, pp. 141-145, 2010.
[10]. Z. Yun-peng, Z. Zheng-jun, L. Wei, N. Xuan, C.
Shui-ping and D. Wei-di. Digital Image
Encryption Algorithm Based on Chaos and Improved DES.In Proc. of the IEEE International
Conference on Systems, Man, and Cybernetics, San Antonio, TX, USA, pp.
474-479, October 2009.
[11]. Asha P.
Choudhari (Asst. Prof)MITAOE Alndi “Information
Hiding in Video using CDCS and Adaptive Embedding”, 2013.
[12] N.Ahmed,T.Natrajan,and K.
R. Rao,”On Image Processing and a Discrete Cosine Transform, IEEE Transactions
Computers C-vol 23, no. 1, 1974, pp. 90-93.
[13].SaadBouguezel, M. Omair Ahmad, and M.N.S.
Swamy, “Low-Complexity 8×8
Transform for ImageCompression,” ElectronicsLetters, vol. 44, Oct. 2008.
[14]. SaadBouguezel, M. Omair
Ahmad, and M.N.S. Swamy, “A fast 8×8 transform for image compression,” IEEE
International Conference on Microelectronics (ICM’2009), Marrakech, Morocco,
Dec. 2009, pp.74-77.
[15]. Barnali
Gupta Banik “A DWT Method for
Image Steganography” Volume 3, Issue 6,
June 2013.
[16].Ms. Hemlata Sharma,Ms. Mithlesh Arya, Mr. Dinesh Goyal
“Secure Image Hiding Algorithm using
Cryptography and Steganography” Volume
13, Issue 5 (Jul. - Aug. 2013), PP 01-06.
[17] Won-Hee kim,Tae-II Jeong and Jong-Nam Kim “Video
Segmentation Algorithm Using Threshold and Weighting Based on Moving Sliding
Window” ICACT,2009,pp. 1781-1784.
[18] Ram Kumar
Yadav “Deformation and Improvement of Video Segmentation Based on morphology
Using SSD Technique” Ram Kumar Yadhav et al, Int. J. Comp. Tech. Appl.,
Vol 2 (5), 1322-1327
[19]. Dr.
Nabeel Hashem Kaghed Dr. Tawfiq A. Abbas Wafaa Hassan AL-Marsomi “Video Clip
Image Compression Using DCT Technique” University of Babylon, Iraq.
[20]. Dr. Suresh N.
Mali ,Content Security Enhancement by Effective Encryption and Sealed
Steganography, Ph.D. Thesis.