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Implementation of High-Speed Pseudo-Random-Number Generator with Chaotic and Random Neural Networks

2020 | HICSS | Citations: 0
Authors: Yoshida, Hitoaki; Fukuchi, Haruka; Murakami, Takeshi

Abstract: Chaotic and random time series generated from improved chaotic and random neural ... Expand

Abstract: Chaotic and random time series generated from improved chaotic and random neural network (CRNN) afford statistically appropriate pseudo-random number series for information security. Randomness of outputs of CRNN is empirically validated in detail, and control methods of an appropriate ratio of chaotic character and randomness in the time series for PRNG is reported. The rate of random number generation has reached 2.8530×1012 b/s. In future, the generator may play an important role on implementing applications for protecting personal information on the Internet. Collapse

Semantic filters: high-performance computing data security

Topics: data security logistics management high-performance computing

Methods: longitudinal research time series analysis descriptive statistic experiment correlation analysis

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