Yoshida, HitoakiFukuchi, HarukaMurakami, Takeshi2020-01-042020-01-042020-01-07978-0-9981331-3-3http://hdl.handle.net/10125/64528Chaotic 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 2.8530×10^12 b/s. In future, the generator may play an important role on implementing applications for protecting personal information on the Internet.8 pagesengAttribution-NonCommercial-NoDerivatives 4.0 InternationalDesigning Digitally Responsible System, Software and Services Engineeringchaosgpuinformation securitypseudo-random numberrandomnessConference Paper10.24251/HICSS.2020.786