2021 ◽  
Vol 11 (8) ◽  
pp. 3330
Author(s):  
Pietro Nannipieri ◽  
Stefano Di Matteo ◽  
Luca Baldanzi ◽  
Luca Crocetti ◽  
Jacopo Belli ◽  
...  

Random numbers are widely employed in cryptography and security applications. If the generation process is weak, the whole chain of security can be compromised: these weaknesses could be exploited by an attacker to retrieve the information, breaking even the most robust implementation of a cipher. Due to their intrinsic close relationship with analogue parameters of the circuit, True Random Number Generators are usually tailored on specific silicon technology and are not easily scalable on programmable hardware, without affecting their entropy. On the other hand, programmable hardware and programmable System on Chip are gaining large adoption rate, also in security critical application, where high quality random number generation is mandatory. The work presented herein describes the design and the validation of a digital True Random Number Generator for cryptographically secure applications on Field Programmable Gate Array. After a preliminary study of literature and standards specifying requirements for random number generation, the design flow is illustrated, from specifications definition to the synthesis phase. Several solutions have been studied to assess their performances on a Field Programmable Gate Array device, with the aim to select the highest performance architecture. The proposed designs have been tested and validated, employing official test suites released by NIST standardization body, assessing the independence from the place and route and the randomness degree of the generated output. An architecture derived from the Fibonacci-Galois Ring Oscillator has been selected and synthesized on Intel Stratix IV, supporting throughput up to 400 Mbps. The achieved entropy in the best configuration is greater than 0.995.


VLSI Design ◽  
2010 ◽  
Vol 2010 ◽  
pp. 1-11 ◽  
Author(s):  
JunKyu Lee ◽  
Gregory D. Peterson ◽  
Robert J. Harrison ◽  
Robert J. Hinde

The Scalable Parallel Random Number Generators (SPRNGs) library is widely used in computational science applications such as Monte Carlo simulations since SPRNG supports fast, parallel, and scalable random number generation with good statistical properties. In order to accelerate SPRNG, we develop a Hardware-Accelerated version of SPRNG (HASPRNG) on the Xilinx XC2VP50 Field Programmable Gate Arrays (FPGAs) in the Cray XD1 that produces identical results. HASPRNG includes the reconfigurable logic for FPGAs along with a programming interface which performs integer random number generation. To demonstrate HASPRNG for Reconfigurable Computing (RC) applications, we also develop a Monte Carlo π-estimator for the Cray XD1. The RC Monte Carlo π-estimator shows a 19.1× speedup over the 2.2 GHz AMD Opteron processor in the Cray XD1. In this paper we describe the FPGA implementation for HASPRNG and a π-estimator example application exploiting the fine-grained parallelism and mathematical properties of the SPRNG algorithm.


2014 ◽  
Vol 1 ◽  
pp. 272-275 ◽  
Author(s):  
Vincent Canals ◽  
Antoni Morro ◽  
Josep L. Rosselló

2013 ◽  
Vol 61 (3) ◽  
pp. 691-696 ◽  
Author(s):  
R. Suszynski ◽  
K. Wawryn

Abstract A rapid prototyping method for designing mixed signal systems has been presented in the paper. The method is based on implementation of the field programmable analog array (FPAA) to configure and reconfigure mixed signal systems. A serial algorithmic analog digital converter has been used as an example. Three converter architectures have been selected and implemented FPAA device. To verify and illustrate converters operation and prototyping capabilities, implemented converters have been excited by a sinusoidal signal. Analog sinusoidal excitations, digital responses and sinusoidal waveforms after reconstruction are presented.


1991 ◽  
Vol 26 (12) ◽  
pp. 1860-1867 ◽  
Author(s):  
E.K.F. Lee ◽  
P.G. Gulak

2021 ◽  
Vol 485 ◽  
pp. 126736
Author(s):  
Muhammad Imran ◽  
Vito Sorianello ◽  
Francesco Fresi ◽  
Bushra Jalil ◽  
Marco Romagnoli ◽  
...  

2015 ◽  
Vol 137 ◽  
pp. 828-836 ◽  
Author(s):  
Che-Chi Shu ◽  
Vu Tran ◽  
Jeremy Binagia ◽  
Doraiswami Ramkrishna

Sign in / Sign up

Export Citation Format

Share Document