Data encryption is widely used to assure security in open networks such as the internet. Each kind of data has
its own features; therefore, different techniques should be used to protect confidential data from unauthorized access.
Currently, most of the available encryption algorithms are used for text data. However, due to large data size and real time
constrains, algorithms that are good for textual data may not be suitable for multimedia data. This Paper is a literature
survey about block ciphers encryption algorithm( triple-DES, DES,AES, Blow-Fish).In this Paper I have concentrates on
providing a starting point for designing strong, secure, and efficient cryptosystems. Various design issues and algorithms
have been described in the paper. Paper explains a new timing evaluation model based on random number generating
mechanism is proposed here to analyze the time-consuming of the known block cipher symmetric cryptographic
algorithms. In this model for evaluation, there is one evaluating mode, which is different plaintexts in the same key
(DPSK). As the basis of the evaluating model, the plaintext and the corresponding key, both generated by random
numbers. The theoretical results shows that under the same key length and for the same size of the processed data, Triple-
DES is about several hundred times slower than our proposed working model, AES, DES, Blow-Fish and IDEA. And
there are other runtime characteristics which further highlight the difference between these three cryptographic
algorithms and provide a reference value of for people’s rational using.
Published In:IJCSN Journal Volume 6, Issue 3
Date of Publication : June 2017
Pages : 425-429
Tables : --
Mayank Kumar Rusia : holds Master of Technology degree
specialization in Artificial Intelligence in the Department of Information
Technology awarded in the year 2011. He has done Bachelor of
Engineering in Information Technology, awarded in the year 2005.
The author is presently working as a Lecturer (Senior Scale), being
the in-charge Head of Department for Computer Science and
Engineering Department at S.R. Government Polytechnic College,
Sagar, Madhya Pradesh, governed by Directorate of Technical
Education, Government of Madhya Pradesh, India.
Mohit Rusia : being the Master of Engineer in Information Security in
the branch of Information Technology awarded in the year 2014 and
Bachelor of Engineer in Computer Science and Engineering stream,
awarded in year 2012, works in a MNC as a Senior Information
Security Analyst at National Capital Region, New Delhi, India.
Time-Consuming; Triple-DES; AES; Blow-Fish; IDEA; Random Number.
That is what most theoretical analysis cannot achieve,
even though quite familiar with the algorithm. When
the number of the evaluated plaintexts is bigger, their
effect is more obvious. Finally, it is not difficult to find
that, in contrast with training data, the larger the key
length is, the bigger AVT is, especially for Triple-DES.
This is also indicating that Blow-Fish is the most
effective algorithm except proposed working model due
to fixed key size and the value of MAX or MIN is not
the same in evaluation mode. Besides, in contrast with
training data, it is not difficult to find that the
increasing key length can lead to the significant
increment of AVT. In fact, different value of MAX and
MIN further manifest that not only the resulting cipher
text depends on the key; the content of key also effects
the time consuming of algorithm.
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Technique”, Department of Computer
Science,University of Wollongong Australia,
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Network Security, VOL.8 No.12, December 2008.
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Kader, and Mohiy Mohamed Hadhoud, “Evaluating The
Performance of Symmetric Encryption Algorithms”,
International Journal of Network Security, Vol.10, No.3,
PP.213-219, May 2010.
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and Mohiy Mohamed Hadhoud, “Evaluating the Effects
of Symmetric Cryptography Algorithms on Power
Consumption for Different Data Types”, International
Journal of Network Security, Vol.11, No.2, PP.78-87,
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Artech House Publishers, 2005.
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known cryptographic algorithms”, published in 2009
International Conference on Computational Intelligence
and Security978-0-7695-3931-7/09 IEEE DOI
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