A Lightweight Pseudo-Random Number Generator Based on a Robust Chaotic Map

2020 ◽  
Author(s):  
Imad El Hanouti ◽  
Hakim El Fadili ◽  
Wahid Souhail ◽  
Fawad Masood
Keyword(s):  
Random Number ◽  
Chaotic Map ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo 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.

Pseudo random number generator based on quantum chaotic map

2014 ◽  
Vol 19 (1) ◽  
pp. 101-111 ◽  
Author(s):  
A. Akhshani ◽  
A. Akhavan ◽  
A. Mobaraki ◽  
S.-C. Lim ◽  
Z. Hassan
Keyword(s):  
Random Number ◽  
Chaotic Map ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

PSEUDO-RANDOM NUMBER GENERATOR BASED ON COUPLED MAP LATTICES

2004 ◽  
Vol 18 (17n19) ◽  
pp. 2409-2414 ◽  
Author(s):  
HUAPING LÜ ◽  
SHIHONG WANG ◽  
GANG HU
Keyword(s):  
Random Number ◽  
Chaotic Map ◽  
Random Number Generator ◽  
Coupled Map Lattices ◽  
Random Numbers ◽  
Secure Communications ◽  
Number Generator ◽  
Generator System ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

A one-way coupled chaotic map lattice is used for generating pseudo-random numbers. It is shown that with suitable cooperative applications of both chaotic and conventional approaches, the output of the spatiotemporally chaotic system can easily meet the practical requirements of random numbers, i.e., excellent random statistical properties, long periodicity of computer realizations, and fast speed of random number generations. This pseudo-random number generator system can be used as ideal synchronous and self-synchronizing stream cipher systems for secure communications.

scholarly journals Chaos Based Cryptographic Pseudo-Random Number Generator Template with Dynamic State Change

2020 ◽  
Vol 10 (2) ◽  
pp. 451 ◽  
Author(s):  
Octaviana Datcu ◽  
Corina Macovei ◽  
Radu Hobincu
Keyword(s):  
Random Number ◽  
Color Image ◽  
Statistical Tests ◽  
Chaotic Map ◽  
Random Number Generator ◽  
Monte Carlo Analysis ◽  
Dynamic State ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

This article presents a configurable, high-throughput pseudo-random number generator template targeting cryptographic applications. The template is parameterized using a chaotic map that generates data, an entropy builder that is used to periodically change the parameters of the map and a parameter change interval, which is the number of iterations after which the entropy builder will change the generator’s parameters. The system is implemented in C++ and evaluated using the TestU01 and NIST RNG statistical tests. The same implementation is used for a stream cipher that can encrypt and decrypt PNG images. A Monte-Carlo analysis of the seed space was performed. Results show that for certain combinations of maps and entropy builders, more than 90% of initial states (seeds) tested pass all statistical randomness tests. Also, the throughput is large enough so that a 8 K color image can be encrypted in 2 s on a modern laptop CPU (exact specifications are given in the paper). The conclusion is that chaotic maps can be successfully used as a building block for cryptographic random number generators.

Design of pseudo-random number generator from turbulence padded chaotic map

2021 ◽  
Author(s):  
Sathya Krishnamoorthi ◽  
Premalatha Jayapaul ◽  
Rajesh Kumar Dhanaraj ◽  
Vani Rajasekar ◽  
Balamurugan Balusamy ◽  
...  
Keyword(s):  
Random Number ◽  
Chaotic Map ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

scholarly journals Low power pseudo-random number generator based on lemniscate chaotic map

2021 ◽  
Vol 11 (1) ◽  
pp. 863
Author(s):  
Mohamed Saber ◽  
Marwa M. Eid
Keyword(s):  
Low Power ◽  
Random Number ◽  
Chaotic Map ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Proposed Model ◽  
Wide Range ◽  
Field Programmable ◽  
Pseudo Random Number Generator

Lemniscate chaotic map (LCM) provides a wide range of control parameters, canceling the need for several rounds of substitutions, and excellent performance in the confusion process. Unfortunately, the hardware model of LCM is complex and consumes high power. This paper presents a proposed low power hardware model of LCM called practical lemniscate chaotic map (P-LCM) depending on trigonometric identities to reduce the complexity of the conventional model. The hardware model designed and implement into the field programmable gate array (FPGA) board, Spartan-6 SLX45FGG484-3. The proposed model achieves a 48.3 % reduction in used resources and a 34.6 % reduction in power consumption compared to the conventional LCM. We also introduce a new pseudo-random number generator based on a proposed low power P-LCM model and perform the randomization tests for the proposed encryption system.

scholarly journals New pseudo-random number generator based on improved discrete-space chaotic map

Filomat ◽  
2019 ◽  
Vol 33 (8) ◽  
pp. 2257-2268 ◽  
Author(s):  
Dragan Lambic ◽  
Mladen Nikolic
Keyword(s):  
Random Number ◽  
Linear Time ◽  
Chaotic Map ◽  
Random Number Generator ◽  
Discrete Space ◽  
Test Suite ◽  
Security Level ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

In this paper, a new pseudo-random number generator (PRNG) based on improved onedimensional discrete-space chaotic map is proposed. Like the original, the improved map relies on bijective mapping of permutations and natural numbers. Instead of using standard Lehmer code, we use a mapping computable in linear time, which significantly speeds up the PRNG. Results of NIST 800-22 test suite and TestU01 test suite confirm that the proposed approach can be used for generation of pseudo-random numbers. Due to discrete nature of used chaotic map, the proposed PRNG is not influenced by dynamical degradation and has virtually unlimited key space. Proposed approach has much better ratio between required memory and security level than previous secure one-dimensional discrete-space chaotic PRNGs. Also, proposed PRNG is much faster than other secure PRNGs of the same type. Satisfactory speed and small memory requirements indicate that proposed PRNG has properties desirable for use in devices with limited memory space, such as wireless sensor networks.

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