Presented by Anu Mattatholi

A DETAILED SURVEY ON TEXT DATA SECURITY
AND COMPRESSION TECHNIQUES USING
HUFFMAN CODING COMPRESSION
AUTHOR
ANU MATTATHOLI
MPhil COMPUTER SCIENCE(FT)
NASC
CO-AUTHOR
DR.N. KAVITHA(HOD)
DEPT. OF CS
NASC
COIMBATORE

OBJECTIVE
 Data Security and Compression is much
helpful for effective data management.
 Compression process saves storage space and
makes easy transmission.
 For text data compression, the best technique
ever used is Huffman Coding.
 It is an optimal technique used in both lossy
and lossless data.

WHAT THIS PAPER IS ABOUT??
 This paper gives you a comprehensive analysis
on existing data compression techniques.
 The analysis focus mainly on Huffman coding,
and also provides direction to solve problems
of such systems.

Index Terms
 Data Compression
 Data Security
 Huffman Coding
 Lossless data Compression

Introduction
 Due to internet applications, digital data flow
became very huge and occupied more storage
space.
 So its difficult to handle data because of this
huge size.
 How this should be overcome???

Continuation…
 Using Data Compression.
 This will be the best way to achieve high
security and can reduce storage space with
less transaction time.

Continuation…
 On which file format data level security can be
performed??
 In text , image, audio, video etc….
 In this paper ,text data security and
compression techniques are analyzed.

Process flow involved……
Block Diagram
Source Data
Multilevel Security
Compression Decompression
Compressed Data

Continuation…
Data Compression
Lossy
Compression
(Most effective)
Lossless
Compression
(Used in this
paper)

Techniques Used for Data Compression
 Both takes stream of symbols and transform into codes.
 The stream code size will determine the effectiveness of
compression.
 If code size is less than original the compression is effective.
Two step process
Modeling
Coding

Continuation…
Lossless data compression
Statistical
Reads single symbol using
probability of character
appearance
Dictionary
based
Uses a single code to replace
string of symbols. Coding
problem is reduced.

Huffman Coding
 Really popular method for effective data
compression.
 Types of Huffman Coding : Adaptive Huffman
Coding, Shannon entropy, Run-length
encoding and so on….
 Uses prefix code generation process.
 Creates a binary tree and generates different
symbols with probability.

Continuation….
 An unique prefix code is assigned to each
symbol.
 Static Huffman Coding reads data twice. One
for initially calculating frequency and next for
reading the content again.
 In Dynamic Huffman coding, it starts with
empty tree and modifies.
 Compression and Decompression change the
tree in a same way that used for compression.

Boon while Using Huffman Coding
 Paper[5],Distributed Data Aggregation Service
have been implemented using Adaptive
Huffman Coding using the authentication
protocol Kerberos.
 It increases the security and ensures that
authorized client is able to access distributed
database.

Continuation…
• Paper[6],Huffman coding improves data
security and reduces the size of high
dimensional data array.
• Paper[7], Lossless methods of Huffman Coding
technique has achieved fast data compression
and converts into confidential data array.
• Paper[8],Bit-stuffing and Huffman coding can
provide high level security and performance
on compression processes.
• It reduces transmission time and bandwidth
utilization.

Curse while using Huffman Coding
 Difficult to execute at some while…
 Sometimes the binary tree implementation
shouldn’t give accurate result.

Conclusion
• The analysis of encoding techniques and tools for
compression is discussed.
• This paper specifically concentrated on Huffman
Coding related works and its drawbacks.
• Survey gives technique for text data.
• Huffman Coding is popular, but execution issues
arises.
• This paper gives idea about such issues in brief.
• From this analysis, an optimal solution can be found.

References
[1] Sayood, Khalid. Introduction to data compression. Morgan Kaufmann, 2017.
[2]Chang, Weiling, Binxing Fang, Xiaochun Yun, and Shupeng Wang. "The block lossless data
compression algorithm." International Journal of Computer Science and Network Security
(IJCSNS) 9, no. 10 (2009): 116.
[3]Sharma, Neha, Jasmeet Kaur, and Navmeet Kaur. "A review on various Lossless text data
compression techniques." International Journal of Engineering Sciences, Issue 2 (2014).
[4]Chau, Savio N., and Ridwan Rashid. "Data compression with Huffman code on multicore
processors." U.S. Patent 9,258,013, issued February 9, 2016.
[5]Gulhane, Suraj, and Sonali Bodkhe. "DDAS using Kerberos with Adaptive Huffman Coding to
enhance data retrieval speed and security." In Pervasive Computing (ICPC), 2015 International
Conference on, pp. 1-6. IEEE, 2015.
[6]Sarkar, Subhra J., Nabendu Kr Sarkar, and Antra Banerjee. "A novel Huffman coding based
approach to reduce the size of large data array." In Circuit, Power and Computing
Technologies (ICCPCT), 2016 International Conference on, pp. 1-5. IEEE, 2016.
[7]Hameed, Maan, Asem Khmag, Fakhrul Zaman, and Abd Rahman Ramli. "A New Lossless
Method of Huffman Coding for Text Data Compression and Decompression Process with
FPGA Implementation." Journal of Engineering and Applied Sciences 100, no. 3 (2016): 402-
407.
[8]Kodabagi, M. M., M. V. Jerabandi, and Nagaraj Gadagin. "Multilevel security and compression
of text data using bit stuffing and huffman coding." In Applied and Theoretical Computing and
Communication Technology (iCATccT), 2015 International Conference on, pp. 800-804. IEEE,
2015.

Presented by Anu Mattatholi

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