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A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map
Micromachines, Volume: 12, Issue: 1, Start page: 31
Swansea University Author: Scott Yang
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DOI (Published version): 10.3390/mi12010031
Abstract
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, wh...
Published in: | Micromachines |
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ISSN: | 2072-666X |
Published: |
MDPI AG
2020
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa58944 |
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Abstract: |
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. |
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Keywords: |
stochastic computing; chaos; logistic map; FPGA |
College: |
Faculty of Science and Engineering |
Funders: |
This research was partially supported by the National Natural Science Foundation of China under Grants 61661008 and 61801131, the funding of Overseas 100 Talents Program of Guangxi Higher Education, the Diecai Project of Guangxi Normal University, 2018 Guangxi One Thousand Young and Middle-Aged College and University Backbone Teachers Cultivation Program, and research fund of Guangxi Key Lab of Multi-source Information Mining & Security (19-A-03-02) |
Issue: |
1 |
Start Page: |
31 |