FPGA Implementation of a Pseudorandom Number Generator Based on k – Logistic Map

2020 ◽  
Author(s):  
Matheus M. de A. Kotaki ◽  
Maximiliam Luppe
Keyword(s):  
Logistic Map ◽  
Fpga Implementation ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Number Generator

scholarly journals A New Two-Dimensional Mutual Coupled Logistic Map and Its Application for Pseudorandom Number Generator

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Xuan Huang ◽  
Lingfeng Liu ◽  
Xiangjun Li ◽  
Minrong Yu ◽  
Zijie Wu
Keyword(s):  
Statistical Tests ◽  
Chaotic Map ◽  
Logistic Map ◽  
Security Analysis ◽  
Three Dimensional ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Two Dimensional ◽  
Practical Applications

Given that the sequences generated by logistic map are unsecure with a number of weaknesses, including its relatively small key space, uneven distribution, and vulnerability to attack by phase space reconstruction, this paper proposes a new two-dimensional mutual coupled logistic map, which can overcome these weaknesses. Our two-dimensional chaotic map model is simpler than the recently proposed three-dimensional coupled logistic map, whereas the sequence generated by our system is more complex. Furthermore, a new kind of pseudorandom number generator (PRNG) based on the mutual coupled logistic maps is proposed for application. Both statistical tests and security analysis show that our proposed PRNG has good randomness and that it can resist all kinds of attacks. The algorithm speed analysis indicates that PRNG is valuable to practical applications.

A novel pseudorandom number generator based on pseudorandomly enhanced logistic map

2016 ◽  
Vol 87 (1) ◽  
pp. 407-425 ◽  
Author(s):  
M. A. Murillo-Escobar ◽  
C. Cruz-Hernández ◽  
L. Cardoza-Avendaño ◽  
R. Méndez-Ramírez
Keyword(s):  
Logistic Map ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Number Generator

A Pseudorandom Number Generator Based on a 4D Piecewise Logistic Map with Coupled Parameters

2019 ◽  
Vol 29 (09) ◽  
pp. 1950124
Author(s):  
Yong Wang ◽  
Zhiqiang Zhang ◽  
Guodong Wang ◽  
Dong Liu
Keyword(s):  
Density Distribution ◽  
Probability Density ◽  
Logistic Map ◽  
Pseudorandom Number ◽  
Parallel Structure ◽  
Basic Unit ◽  
Probability Density Distribution ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Chaotic Model

The piecewise logistic map (PLM) is an improved version of logistic map, which is specifically designed for cryptographic application. However, the probability density distribution of PLM is not uniform. To overcome this shortage, a parameter-coupled piecewise logistic map (PCPLM) is presented. Using the PCPLM as a basic unit, we construct a four-dimensional chaotic model, which has even probability density distribution. The four-dimensional chaotic model based on PCPLMs also has a parallel structure, which is beneficial to enhancing the running efficiency. Finally, a novel pseudorandom number generator (PRNG) is presented based on this four-dimensional chaotic model. The security analysis and simulation tests on the proposed PRNG are performed. The results both confirm that the proposed PRNG is secure and efficient. Therefore, it can be used as a candidate for data security.

A pseudorandom number generator based on piecewise logistic map

2015 ◽  
Vol 83 (4) ◽  
pp. 2373-2391 ◽  
Author(s):  
Yong Wang ◽  
Zhaolong Liu ◽  
Jianbin Ma ◽  
Haiyuan He
Keyword(s):  
Logistic Map ◽  
Pseudorandom Number ◽  
Pseudorandom Number Generator ◽  
Number Generator
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