1. A Seminar on
Mini-project
An Efficient Encryption using Data Compression towards
Steganography
.
Presented by
Prashant Dahake
Mtech CSE
Dept. of Computer Science & Engineering
2013-2014
1 1
1

2. Outlines







Introduction
Review of Literature
Methodology
Block Diagram of Proposed System
Research Contribution
Conclusion
References

3. Introduction
 Data transmission must be secure enough
to be used in channel
medium without any loss and tampering of data. Secure transmission of
data is a key issue in the field of information technology.[2]
 Data sent must be in compact way. Compactness is achieve through
data compression, which reduces storage space or transmission capacity
of the information.
 Data compression is formally called as bit rate reduction. Which
focuses on reducing the number of bits representing the secret
information.
Types of data compression
 Lossy
 Lossless

4. Review of literature
Sr.
No
Author
Title
Methodology
Inference Drawn
1
K. Ashok
Babu and V.
Satish Kumar
Implementation of
Data Compression
Using Huffman
Coding.2010 [3]
It makes an use of
probability
of
occurrence of each
character
in the
message.
 Use tree structure
and top down
approach
 Each symbol is
represented
by
variable length code
 not that much
efficient.
G.
Manikandan,
N. Sairam
and M.
Kamarasan
A Hybrid Approach
for Security
Enhancement by
Compressed
Crypto-Stegno
Scheme
(2012)[9]
 LZW (LempelZiv-Welch)
algorithm
 uses Dictionary
It replaces strings
of characters with
single Code
2

5. Continue…..
Sr.
No.
3
4
Author
Title
Asjad Amin,
Haseeb
Ahmad
Qureshi,
Muhammad
Junaid
Run Length Encoding
Scheme with
Introduction of Bit
Stuffing for efficient
Data Compression
(2011)[7]
M.S.Sutaone,
M.V.
Khandare
Image based
steganography using
LSB insertion
technique [2008]
Methodology
• RLE
algorithm
• Uses LSB
technique.
(without any
compression
technique)
Inference Drawn
 Consecutive
bits are counted
and
store
as
single value with
its run.
 not
always
produce
compression
 when size of the
data increases, one
can
identify
difference
between images

6. Methodology
 Arithmetic coding compression technique is used. It converts
stream of plaintext into single floating point number[1] and range of
floating point number is between [0,1].
 It has high compression ratio than any other compression
technique.

 It is based on probability of each character[2]. Calculated as
Where P= probability of character
C= Occurrence of the character
L= Length of the plaintext

7. Fig. 1 Working of Arithmetic Coding

8. Block diagram of proposed system
PLANE TEXT
ARITHMETIC CODING
DATA COMPRESSION
FLOATING POINT
NUMBER
BINARY
CODED FORM
ENCRYPTION
IMAGE
BINARY
CODED FORM
STEGANOGRAPHY
(EMBEDDING)
Fig. 2 Process at Sender side
STEGO IMAGE

9. CONTINUE…
STEGO-IMAGE
BINARY
CODED
FORM
PLANE TEXT
STEGANOGRAPHY
(EXTRACTION)
ARITHMETIC
CODING
DECOMPRESSION
Fig.3 Process at Receiver side
DECRYPTION
FLOATING
POINT NUMBER

10. Research Contribution
 Compactness is achieved using Data compression technique, that is by
using arithmetic coding. It provide some amount of security to secret data.
 But in proposed system additional security is provided to data by using
Encryption technique , which makes an use of any cryptographic algorithm
and it is applied on the compressed data.
 Provides confidentiality and secrecy to data.

11. Conclusion
 Thus the proposed system can provides an efficient manner for
the transmission of the secret information from one authorized user
to the other.
 From the study of literature, Compressed data required less
storage capacity, so more amount of information can be hided inside
the image.

12. References
[1] Jiantao Zhou, Xianming Liu, Oscar C. Au, Fellow, and Yuan Yan Tang,
Fellow, “Designing an Efficient Image Encryption-Then-Compression System
via Prediction Error Clustering and Random Permutation”, IEEE Transactions
on information forensic and security,vol.9,No.1,january 2014.
[2] M. Gomathymeenakshi, S. Sruti, B. Karthikeyan, Meka Nayana, “An
Efficient Arithmetic Coding Data Compression with Steganography”, IEEE
International Conference on Emerging Trends in Computing, Communication
and Nanotechnology, 2013.
[3] K. Ashok Babu and V. Satish Kumar, “Implementation of Data
Compression Using Huffman Coding”, Methods and Models in Computer
Science (ICM2CS), 2010 International Conference on , vol., no., pp.70,75, 1314 Dec. 2010.
[4] Monica Adriana Dagadit, Emil Ioan Slusanschi ,Razvan Dobre, “Data
Hiding Using Steganography”, IEEE 12th International Symposium on
Parallel and Distributed Computing, 2013.
[5] O. P Verma, Ritu Agarwal, Dhiraj Dafouti, Shobha Tyagi, “Peformance
Analysis Of Data Encryption Algorithms”, IEEE 2011.

13. [6] Jyoti Gaba, R.C. Mishra, “A Review Based Study of Hybrid Security Schemes
Based on Compression, Encryption and Steganography”,International Journal of
Engineering Trends and Technology (IJETT) – Volume 4 Issue 7- July 2013.
[7] Asjad Amin, Haseeb Ahmad Qureshi, Muhammad Junaid, “Run Length
Encoding Scheme with Introduction of Bit Stuffing for efficient Data
Compression”, International Conference for internet Technology and Secured
Transactions,2011.
[8] Senthil Shanmugasundaram, Robert Lourdusamy, “A Comparative Study Of
Text Compression Algorithms”, International Journal of Wisdom Based
Computing, Vol. 1 (3), December 2011.
[9] G. Manikandan, N. Sairam and M. Kamarasan, “A Hybrid Approach for
Security Enhancement by Compressed Crypto-Stegno Scheme”, Research Journal
of Applied Sciences, Engineering and Technology 4(6): 608-614, 2012.