6533b83afe1ef96bd12a7ae2
RESEARCH PRODUCT
Random Walk in a N-cube Without Hamiltonian Cycle to Chaotic Pseudorandom Number Generation: Theoretical and Practical Considerations
Christophe GuyeuxChristophe GuyeuxSylvain Contassot-vivierPierre-cyrille HéamPierre-cyrille HéamJean-françois CouchotJean-françois Couchotsubject
FOS: Computer and information sciencesUniform distribution (continuous)Computer Science - Cryptography and SecurityComputer scienceHamiltonian CycleChaoticPseudorandom Numbers GeneratorFOS: Physical sciences02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]01 natural sciencesUpper and lower bounds[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computingsymbols.namesake[INFO.INFO-MC]Computer Science [cs]/Mobile Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0202 electrical engineering electronic engineering information engineeringApplied mathematics[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]0101 mathematicsEngineering (miscellaneous)Pseudorandom number generatorChaotic IterationsBasis (linear algebra)Applied Mathematics020208 electrical & electronic engineering010102 general mathematicsRandom walkNonlinear Sciences - Chaotic DynamicsHamiltonian path[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationNonlinear Sciences::Chaotic Dynamics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Modeling and SimulationRandom Walk[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]symbolsPseudo random number generator[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Chaotic Dynamics (nlin.CD)[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Cryptography and Security (cs.CR)description
Designing a pseudorandom number generator (PRNG) is a difficult and complex task. Many recent works have considered chaotic functions as the basis of built PRNGs: the quality of the output would indeed be an obvious consequence of some chaos properties. However, there is no direct reasoning that goes from chaotic functions to uniform distribution of the output. Moreover, embedding such kind of functions into a PRNG does not necessarily allow to get a chaotic output, which could be required for simulating some chaotic behaviors. In a previous work, some of the authors have proposed the idea of walking into a $\mathsf{N}$-cube where a balanced Hamiltonian cycle has been removed as the basis of a chaotic PRNG. In this article, all the difficult issues observed in the previous work have been tackled. The chaotic behavior of the whole PRNG is proven. The construction of the balanced Hamiltonian cycle is theoretically and practically solved. An upper bound of the expected length of the walk to obtain a uniform distribution is calculated. Finally practical experiments show that the generators successfully pass the classical statistical tests.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2017-02-10 |