Ant Colony-Inspired Parallel Algorithm to Improve Cryptographic Pseudo Random Number Generators

2017 ◽  
Author(s):  
Jorg Keller ◽  
Gabriele Spenger ◽  
Steffen Wendzel
Keyword(s):  
Parallel Algorithm ◽  
Random Number ◽  
Ant Colony ◽  
Random Number Generators ◽  
Pseudo Random Number

Enhanced Ant Colony-Inspired Parallel Algorithm to Improve Cryptographic PRNGs

2017 ◽  
Author(s):  
Jorg Keller ◽  
Gabriele Spenger ◽  
Steffen Wendzel
Keyword(s):  
State Space ◽  
Parallel Algorithm ◽  
Random Number ◽  
Random Number Generator ◽  
Ant Colony ◽  
Massively Parallel ◽  
Power Devices ◽  
Promising Candidate ◽  
Massively Parallel Systems ◽  
Pseudo Random Number Generator

We present and motivate a parallel algorithm to compute promising candidate states for modifying the state space of a pseudo-random number generator in order to increase its cycle length. This is important for generators in low-power devices where increase of state space to achieve longer cycles is not an alternative. The runtime of the parallel algorithm is improved by an analogy to ant colony behavior: if two paths meet, the resulting path is followed at accelerated speed just as ants tend to reinforce paths that have been used by other ants. We evaluate our algorithm with simulations and demonstrate high parallel efficiency that makes the algorithm well-suited even for massively parallel systems like GPUs. Furthermore, the accelerated path variant of the algorithm achieves a runtime improvement of up to 4% over the straightforward implementation.1  

Hardware implementation of pseudo-random number generators based on chaotic maps

2017 ◽  
Vol 90 (3) ◽  
pp. 1661-1670 ◽  
Author(s):  
Luis Gerardo de la Fraga ◽  
Esteban Torres-Pérez ◽  
Esteban Tlelo-Cuautle ◽  
Cuauhtemoc Mancillas-López
Keyword(s):  
Hardware Implementation ◽  
Random Number ◽  
Chaotic Maps ◽  
Random Number Generators ◽  
Pseudo Random Number

scholarly journals Problem of uniqueness in the renewal process generated by the uniform distribution

1992 ◽  
Vol 5 (4) ◽  
pp. 291-305 ◽  
Author(s):  
D. Ugrin-Šparac
Keyword(s):  
Integral Representation ◽  
Uniform Distribution ◽  
Gamma Function ◽  
Renewal Process ◽  
Random Number ◽  
Discrete Distribution ◽  
Inverse Image ◽  
Random Number Generators ◽  
Pseudo Random Number

The renewal process generated by the uniform distribution, when interpreted as a transformation of the uniform distribution into a discrete distribution, gives rise to the question of uniqueness of the inverse image. The paper deals with a particular problem from the described domain, that arose in the construction of a complex stochastic test intended to evaluate pseudo-random number generators. The connection of the treated problem with the question of a unique integral representation of Gamma-function is also mentioned.

scholarly journals Influence of Experiment Design in GPA Investigating with Respect to PRNGs

MENDEL ◽  
2018 ◽  
Vol 24 (2) ◽  
Author(s):  
Tomas Brandejsky
Keyword(s):  
Genetic Programming ◽  
Random Number ◽  
Experiment Design ◽  
Parallel Execution ◽  
Random Number Generators ◽  
Pseudo Random Number ◽  
Programming Algorithms

This paper analyses the influence of experiment parameters onto the reliability of experiments with genetic programming algorithms. The paper is focused on the required number of experiments and especially on the influence of parallel execution which affect not only the order of thread execution but also behaviors of pseudo random number generators, which frequently do not respect recommendation of C++11 standard and are not implemented as thread safe. The observations and the effect of the suggested improvements are demonstrated on results of 720,000 experiments.

Pseudo-random number generators

2003 ◽  
pp. 211-230
Author(s):  
Graham Everest ◽  
Alf van der Poorten ◽  
Igor Shparlinski ◽  
Thomas Ward
Keyword(s):  
Random Number ◽  
Random Number Generators ◽  
Pseudo Random Number
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