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Article

A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map

1
School of Electronic Engineering, Guangxi Normal University, Guilin 541004, China
2
Guangxi Key Lab of Multi-Source Information Mining & Security, Guangxi Normal University, Guilin 541004, China
3
School of Computing and Engineering, University of West London, London W5 5RF, UK
*
Author to whom correspondence should be addressed.
Micromachines 2021, 12(1), 31; https://doi.org/10.3390/mi12010031
Received: 28 November 2020 / Revised: 21 December 2020 / Accepted: 24 December 2020 / Published: 30 December 2020
Recent research showed that the chaotic maps are considered as alternative methods for generating pseudo-random numbers, and various approaches have been proposed for the corresponding hardware implementations. In this work, an efficient hardware pseudo-random number generator (PRNG) is proposed, where the one-dimensional logistic map is optimised by using the perturbation operation which effectively reduces the degradation of digital chaos. By employing stochastic computing, a hardware PRNG is designed with relatively low hardware utilisation. The proposed hardware PRNG is implemented by using a Field Programmable Gate Array device. Results show that the chaotic map achieves good security performance by using the perturbation operations and the generated pseudo-random numbers pass the TestU01 test and the NIST SP 800-22 test. Most importantly, it also saves 89% of hardware resources compared to conventional approaches. View Full-Text
Keywords: stochastic computing; chaos; logistic map; FPGA stochastic computing; chaos; logistic map; FPGA
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MDPI and ACS Style

Liu, J.; Liang, Z.; Luo, Y.; Cao, L.; Zhang, S.; Wang, Y.; Yang, S. A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map. Micromachines 2021, 12, 31. https://doi.org/10.3390/mi12010031

AMA Style

Liu J, Liang Z, Luo Y, Cao L, Zhang S, Wang Y, Yang S. A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map. Micromachines. 2021; 12(1):31. https://doi.org/10.3390/mi12010031

Chicago/Turabian Style

Liu, Junxiu, Zhewei Liang, Yuling Luo, Lvchen Cao, Shunsheng Zhang, Yanhu Wang, and Su Yang. 2021. "A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map" Micromachines 12, no. 1: 31. https://doi.org/10.3390/mi12010031

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