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 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 Cryptographically Secure Pseudo-Random Number Generator IP-Core Based on SHA2 Algorithm

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1869 ◽  
Author(s):  
Luca Baldanzi ◽  
Luca Crocetti ◽  
Francesco Falaschi ◽  
Matteo Bertolucci ◽  
Jacopo Belli ◽  
...  
Keyword(s):  
High Performance ◽  
Random Number ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Random Numbers ◽  
Generation Process ◽  
Number Generator ◽  
Ip Core ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

In the context of growing the adoption of advanced sensors and systems for active vehicle safety and driver assistance, an increasingly important issue is the security of the information exchanged between the different sub-systems of the vehicle. Random number generation is crucial in modern encryption and security applications as it is a critical task from the point of view of the robustness of the security chain. Random numbers are in fact used to generate the encryption keys to be used for ciphers. Consequently, any weakness in the key generation process can potentially leak information that can be used to breach even the strongest cipher. This paper presents the architecture of a high performance Random Number Generator (RNG) IP-core, in particular a Cryptographically Secure Pseudo-Random Number Generator (CSPRNG) IP-core, a digital hardware accelerator for random numbers generation which can be employed for cryptographically secure applications. The specifications used to develop the proposed project were derived from dedicated literature and standards. Subsequently, specific architecture optimizations were studied to achieve better timing performance and very high throughput values. The IP-core has been validated thanks to the official NIST Statistical Test Suite, in order to evaluate the degree of randomness of the numbers generated in output. Finally the CSPRNG IP-core has been characterized on relevant Field Programmable Gate Array (FPGA) and ASIC standard-cell technologies.

Design of a Cryptographically Secure Pseudo Random Number Generator with Grammatical Evolution

2021 ◽  
Author(s):  
Conor Ryan ◽  
Meghana Kshirsagar ◽  
Gauri Vaidya ◽  
Andrew Cunningham ◽  
R Sivaraman
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Grammatical Evolution ◽  
Random Numbers ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Initial Seed ◽  
Discernible Difference ◽  
Pseudo Random Number Generator ◽  
Entropy Source

Abstract This work investigates the potential of evolving an initial seed with Grammatical Evolution (GE), for the construction of cryptographically secure (CS) pseudo-random number generator (PRNG). We harness the flexibility of GE as an entropy source for returning initial seeds. The initial seeds returned by GE demonstrate an average entropy value of 7.920261600000001 which is extremely close to the ideal value of 8. The initial seed combined with our proposed approach, control_flow_incrementor, is used to construct both, GE-PRNG and GE-CSPRNG.The random numbers generated with CSPRNG meet the prescribed National Institute of Standards and Technology (NIST) SP800-22 requirements. Monte Carlo simulations established the efficacy of the PRNG. The experimental setup was designed to estimate the value for pi, in which 100,000,000 random numbers were generated by our system and which resulted in returning the value of pi to 3.146564000, with a precision up to six decimal digits. The random numbers by GE-PRNG were compared against those generated by Python’s rand() function for sampling. The sampling results, when measured for accuracy against twenty-nine real world regression datasets, showed that GE-PRNG had less error when compared to Python’s rand() against the ground truths in seventeen of those, while there was no discernible difference in the remaining twelve.

KOMBINASI LOGISTIC MAP DAN PSEUDO-RANDOM NUMBER GENERATOR PADA PEMBANGKITAN KUNCI UNTUK ENKRIPSI CITRA DIGITAL

2020 ◽  
Vol 25 (3) ◽  
pp. 187-198
Author(s):  
Rini Arianty ◽  
Diana Tri Susetianingtias
Keyword(s):  
Random Number ◽  
Logistic Map ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

Informasi berbentuk gambar yang bersifat sensitif atau rahasia, seperti data pribadi, dokumen penting yang dikirimkan melalui internet belum tentu aman dari serangan pihak luar. Kerugian yang cukup besar dapat ditimbulkan apabila data tersebut diakses dan dimanipulasi oleh orang yang tidak bertanggung jawab. Salah satu metode dalam mengamankan suatu informasi adalah kriptografi. Logistic map adalah salah satu algoritma chaos yang sering digunakan dalam kriptografi citra karena algoritma ini mampu menghasilkan deretan bilangan acak yang kompleks dengan persamaan polinomial rekursif yang sederhana. Pada penelitian ini, akan diimplementasikan algoritma chaos logistic map dan pseudo-random number generator (PRNG) dalam pengenkripsian citra. Citra input akan diubah bentuknya kedalam array lalu proses difusi dilakukan secara selektif dengan mensubstitusi 4 bit MSB setiap nilai warna citra dengan kunci logistic map. Hasil difusi tersebut akan dikonfusi dengan cara mensubstitusikan indeks arraynya dengan kunci prng sehingga didapat sebuah array baru yang teracak indeksnya. Array tersebut diubah kembali menjadi sebuah citra sehingga didapat citra terenkripsi yang aman.

Sign in / Sign up

Export Citation Format

Share Document