NDLI: Efficient and cryptographically secure generation of chaotic pseudorandom numbers on GPU

Content Provider	Springer Nature Link
Author	Guyeux, Christophe Couturier, Raphaël Héam, Pierre Cyrille Bahi, Jacques M.
Copyright Year	2015
Abstract	In this paper, we present a new pseudorandom number generator (PRNG) on graphics processing units (GPU). This PRNG is based on the so-called chaotic iterations. It is firstly proven to be chaotic according to the Devaney’s formulation. We, thus, propose an efficient implementation for GPU that successfully passes the BigCrush tests, deemed to be the hardest battery of tests in TestU01. Experiments show that this PRNG can generate about 20 billion of random numbers per second on Tesla C1060 and NVidia GTX280 cards. It is then established that under reasonable assumptions, the proposed PRNG can be cryptographically secure. A chaotic version of the Blum–Goldwasser asymmetric key encryption scheme is finally proposed.
Starting Page	3877
Ending Page	3903
Page Count	27
File Format	PDF
ISSN	09208542
Journal	The Journal of Supercomputing
Volume Number	71
Issue Number	10
e-ISSN	15730484
Language	English
Publisher	Springer US
Publisher Date	2015-07-14
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Pseudo random number Parallelization GPU Cryptography Chaos Programming Languages, Compilers, Interpreters Processor Architectures Computer Science
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Information Systems Hardware and Architecture Software

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Efficient and cryptographically secure generation of chaotic pseudorandom numbers on GPU