CFP last date
20 May 2024
Reseach Article

True Random Number Generator using Fish Tank Image

by Rajat Katyal, Ankit Mishra, Adarsh Baluni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 78 - Number 16
Year of Publication: 2013
Authors: Rajat Katyal, Ankit Mishra, Adarsh Baluni
10.5120/13609-1419

Rajat Katyal, Ankit Mishra, Adarsh Baluni . True Random Number Generator using Fish Tank Image. International Journal of Computer Applications. 78, 16 ( September 2013), 38-40. DOI=10.5120/13609-1419

@article{ 10.5120/13609-1419,
author = { Rajat Katyal, Ankit Mishra, Adarsh Baluni },
title = { True Random Number Generator using Fish Tank Image },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 78 },
number = { 16 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 38-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume78/number16/13609-1419/ },
doi = { 10.5120/13609-1419 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:45.704183+05:30
%A Rajat Katyal
%A Ankit Mishra
%A Adarsh Baluni
%T True Random Number Generator using Fish Tank Image
%J International Journal of Computer Applications
%@ 0975-8887
%V 78
%N 16
%P 38-40
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A Pseudo Random Number Generator (PRNG) uses a deterministic system and an initial seed to generate random numbers. In order for the output sequence to be truly random, a truly random input seed is used. Most True Random Number Generators (TRNG), use noise in the form nuclear decay, atmospheric noise, electrical noise or Brownian motion as their initial seed. In order to reduce the computational complexity, we use a simple setup of a fish tank as the variable environment, capturing its images over time. The image data is then applied to a reduction algorithm and hash function to generate the initial seed. We propose a cost efficient method of extracting the true seed from the image data and applying it to a pseudo random generator, a Linear Congruential Generator (LCG) in our case to give true random numbers.

References
  1. P. Hellekalek, Good random number generators are (not so) easy to find, Mathematics and Computers in Simulation 46 (1998) 485-505.
  2. Benjamin Jun and Paul Kocher, P. 1999 The Intel Random Number Generator. Technical Report. University of Maryland at College Park.
  3. N. K Pareek, V. Patidar, K. K Sud, A Rndom Bit Generator Using Chaotic Maps, International Journal of Network Security, Vol. 10, no. 1, pp. 32-38, 2010.
  4. Tang, H. C. , "An Analysis of Linear Congruential Random Number Generators when Multiplier Restrictions Exist," European Journal of Operational Research, Vol. 182, pp. 820828 (2007).
  5. Hedayatpour, S. , Chuprat, Suriayati, Hash functions-based random number generator with image data source, Open Systems (ICOS), 2011 IEEE.
  6. Xuan Li, Guoji Zhang, Yuliang Liao, Chaos-based true random number generator using image
  7. P. Murali and R. Palraj, True Random Number Generator Based on Image for Key Exchange program.
  8. Xuan Li; Guoji Zhang; Yuliang Liao, "Chaos-based true random number generator using image," Computer Science and Service System (CSSS), 2011 International Conference on , vol. , no. , pp. 2145,2147, 27-29 June 2011 doi: 10. 1109/CSSS. 2011. 5974933
  9. Matsumoto, M. and T. Nishimura. "Mersenne Twister: A 623-Dimensionally Equidistributed Uniform Pseudorandom Number Generator. " ACM Transactions on Modeling and Computer Simulation 8, no. 1 (1998): 3|30.
  10. Volos, C. K. ; Kyprianidis, I. M. ; Stouboulos, I. N. , "Image encryption process based on a chaotic True Random Bit Generator," Digital Signal Processing, 2009 16th International Conference on , vol. , no. , pp. 1,4, 5-7 July 2009 doi: 10. 1109/ICDSP. 2009. 5201107
  11. Gentle, J. E. Random Number Generation and Monte Carlo Methods, (2nd Ed. ) SpringerVerlag, 2003.
  12. Geman, S. and D. Geman. "Stochastic Relaxation, Gibbs Distributions, and the Bayesian
  13. Restoration of Images. " IEEE Transactions on Pattern Analysis and Machine Intelligence 6, no. 6 (1984): 721|741
  14. Junod, P. "Cryptographic Secure Pseudo-Random Bits Generation: The Blum|Blum|Shub Generator. " August 1999. http://crypto. junod. info/bbs. pdf
Index Terms

Computer Science
Information Sciences

Keywords

True random number generator Image data