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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.
Junxiu Liu; Zhewei Liang; Yuling Luo; Lvchen Cao; Shunsheng Zhang; Yanhu Wang; Su Yang. A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map. Micromachines 2020, 12, 31 .
AMA StyleJunxiu Liu, Zhewei Liang, Yuling Luo, Lvchen Cao, Shunsheng Zhang, Yanhu Wang, Su Yang. A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map. Micromachines. 2020; 12 (1):31.
Chicago/Turabian StyleJunxiu Liu; Zhewei Liang; Yuling Luo; Lvchen Cao; Shunsheng Zhang; Yanhu Wang; Su Yang. 2020. "A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map." Micromachines 12, no. 1: 31.