An algorithm to fill out a bloc with pseudorandom binary data

Authors:
Juan Manuel Garcia Garcia
Affiliations:
Universidad Michoacana de San Nicolás de Hidalgo, División de Estudios de Posgrado, Facultad de Ingeniería Eléctrica, Mexico
Venue:
CEA'10 Proceedings of the 4th WSEAS international conference on Computer engineering and applications
Year:
2010

Citing 9
Cited 0

How to generate cryptographically strong sequences of pseudo-random bits

SIAM Journal on Computing
A simple unpredictable pseudo random number generator

SIAM Journal on Computing
Randomized algorithms and pseudorandom numbers

Journal of the ACM (JACM)
Handbook of Applied Cryptography

Handbook of Applied Cryptography
A Dedicated Circuit for Charged Particles Simulation Using the MonteCarlo Method

Journal of VLSI Signal Processing Systems
Stochastic modeling and quality evaluation of component-based software systems

QSIC '06 Proceedings of the Sixth International Conference on Quality Software
Practical Construction and Analysis of Pseudo-Randomness Primitives

Journal of Cryptology
Parallel Metropolis-Montecarlo Simulation for Potts Model using an Adaptable Network Topology based on Dynamic Graph Partitioning

ISPDC '08 Proceedings of the 2008 International Symposium on Parallel and Distributed Computing
Hardware accelerated montecarlo financial simulation over low cost FPGA cluster

IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Pseudorandom bits generation is very relevant for several fields including Monte-Carlo simulation, procedural generation and applied cryptography. Usually, pseudorandom bits are generated as a sequence, bit by bit. A different approach is followed in this paper, considering how to fill a fixed size bloc with pseudorandom bits. An algorithm to solve this problem as well as pseudorandomness testing results are given. In this new algorithm an input of n bits generates an output of O(2n) pseudorandom bits. Experimental results show that the proposed algorithm generates binary data with good pseudorandom properties.