Cryptanalysis of a Random Number Generator Based on a Chaotic Circuit

2017 ◽  
pp. 370-377 ◽  
Author(s):  
Salih Ergün
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Chaotic Circuit

A novel memristive true random number generator design

2019 ◽  
Vol 38 (6) ◽  
pp. 1931-1947 ◽  
Author(s):  
Zehra Gulru Cam Taskiran ◽  
Murat Taşkıran ◽  
Mehmet Kıllıoğlu ◽  
Nihan Kahraman ◽  
Herman Sedef
Keyword(s):  
Integrated Circuits ◽  
Continuous Time ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Chaotic Circuit ◽  
Flip Flop ◽  
Content Type ◽  
True Random Number Generator ◽  
Chua Circuit

Purpose In this work, a true random number generator is designed by sampling the double-scroll analog continuous-time chaotic circuit signals. Methodology A Chua circuit based on memristance simulator is designed to obtain a non-linear term for a chaotic dynamic system. It is implemented on the board by using commercially available integrated circuits and passive elements. A low precision ADC which is commonly found in the market is used to sample the chaotic signals. The mathematical analysis of the chaotic circuit is verified by experimental results. Originality It is aimed to be one of the pioneering studies (including low precision ADC) in the literature on the implementation of memristive chaotic random number generators. Findings Two new methods are proposed for post-processing and creating random bit array using XOR operator and J-K flip flop. The bit stream obtained by a full-hardware implementation successfully passed the NIST-800-22 test. In this respect, the availability of the memristance simulator circuit, memristive chaotic double-scroll attractor, proposed random bit algorithm and the randomness of the memristive analog continuous-time chaotic true number generator were also verified.

Fuzzy Based Pseudo Random Number Generator used for Wireless Networks

2013 ◽  
Vol 16 (2) ◽  
pp. 210-216 ◽  
Author(s):  
Sattar B. Sadkhan ◽  
◽  
Sawsan K. Thamer ◽  
Najwan A. Hassan ◽  
◽  
...  
Keyword(s):  
Wireless Networks ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

0.4 mW, 0.27 pJ/bit true random number generator using jitter, metastability and current starved topology

2020 ◽  
Vol 14 (7) ◽  
pp. 1001-1011
Author(s):  
Dhirendra Kumar ◽  
Rahul Anand ◽  
Sajai Vir Singh ◽  
Prasanna Kumar Misra ◽  
Ashok Srivastava ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
True Random Number Generator

scholarly journals A High‐Speed True Random Number Generator Based on a Cu x Te 1− x Diffusive Memristor

2021 ◽  
pp. 2100062
Author(s):  
Kyung Seok Woo ◽  
Jaehyun Kim ◽  
Janguk Han ◽  
Jin Myung Choi ◽  
Woohyun Kim ◽  
...  
Keyword(s):  
High Speed ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
True Random Number Generator

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

Micromachines ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 31
Author(s):  
Junxiu Liu ◽  
Zhewei Liang ◽  
Yuling Luo ◽  
Lvchen Cao ◽  
Shunsheng Zhang ◽  
...  
Keyword(s):  
Random Number ◽  
Chaotic Map ◽  
Logistic Map ◽  
Random Number Generator ◽  
Alternative Methods ◽  
Random Numbers ◽  
Number Generator ◽  
Stochastic Computing ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

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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