CFP last date
20 May 2024
Reseach Article

Dynamic Random Number Generator based on User Seed(s)

by Saleh N. Abdullah, Sharaf A. Alhomdy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 118 - Number 3
Year of Publication: 2015
Authors: Saleh N. Abdullah, Sharaf A. Alhomdy
10.5120/20727-3083

Saleh N. Abdullah, Sharaf A. Alhomdy . Dynamic Random Number Generator based on User Seed(s). International Journal of Computer Applications. 118, 3 ( May 2015), 25-28. DOI=10.5120/20727-3083

@article{ 10.5120/20727-3083,
author = { Saleh N. Abdullah, Sharaf A. Alhomdy },
title = { Dynamic Random Number Generator based on User Seed(s) },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 118 },
number = { 3 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 25-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume118/number3/20727-3083/ },
doi = { 10.5120/20727-3083 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:00:42.983785+05:30
%A Saleh N. Abdullah
%A Sharaf A. Alhomdy
%T Dynamic Random Number Generator based on User Seed(s)
%J International Journal of Computer Applications
%@ 0975-8887
%V 118
%N 3
%P 25-28
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Random number generators (RNGs) is an underlying technology to accomplish highly secure systems. Therefore, for any security or simulation, systems should be associated with RNGs. Many of RNGs are currently in use, but the main defects in the available RNGs are the short period of its repeat cycle length and the predefined values of static factors as well. In this paper, we will try to suggest a method to extend the periodic cycle of the repetition and to use dynamic factors instead of static factors based on the seed values for the sake of security enhancement.

References
  1. William Stallings 2009. Cryptography and Network Security: Principles and Practice. 3rd Ed. India Reprint. Agrawal-M IETE-Technical-Review.
  2. Jerry Banks, etc. 2001. Discrete-Event System Simulation. 3rd Ed. Pearson Education. Singapore.
  3. Bruce Schneier 2010. Applied Cryptography. 3rd Ed. John Wiley & Sons. (ASIA) Pvt. Ltd. 2 Clementi Loop # 02-01. Singapore 129809.
  4. Borosh. S. and Niederreiter H. 1983. "Optimal Multipliers For Pseudo-Random Number Generation By The Linear Congruential Method", BIT 23,65-74.
  5. Figiel, K. D. and Sule. D. R. 1985. "New Lagged Product Test for Random Number Generators", Comput. Ind. Eng. Vol. 9, 287-296.
  6. S. Japertas and et al. 2007. "Unpredictable Cryptographic Pseudo-Random Number Generator based on Non-linear Dynamic Chaotic System", Electronics and Electrical Engineering ISSN 1392 – 1215, pp 29 -32.
  7. P. L'Ecuyer 1988. "Efficient and Portable Combined Random Number Generators", Communications of the ACM 31 June 1988, Volume 31 No. 6, USA.
  8. Douglas W. Mitchell 1993. "A Nonlinear Random Number Generator with Known, Long Cycle Length", Cryptologia, Volume 17 Issue 1, pp 55- 62, USA.
Index Terms

Computer Science
Information Sciences

Keywords

Seed Period Static Factors Dynamic Factors RNGs Security Simulation LCM Linear Congruential Uniformity Independence.