scholarly journals Bounds on Fixed Input/Output Length Post-processing Functions for Biased Physical Random Number Generators

2009 ◽  
pp. 373-386 ◽  
Author(s):  
Kyohei Suzuki ◽  
Tetsu Iwata
Keyword(s):  
Random Number ◽  
Post Processing ◽  
Input Output ◽  
Random Number Generators ◽  
Fixed Input

A FPGA-Based Post-Processing and Validation Platform for Random Number Generators

2020 ◽  
Author(s):  
Laurent Gantel ◽  
Alexandre Duc ◽  
Lucie Steiner ◽  
Fabien Vannel ◽  
Andres Upegui ◽  
...  
Keyword(s):  
Random Number ◽  
Post Processing ◽  
Random Number Generators

Study on post-processing algorithms for true random number generators

2021 ◽  
Author(s):  
Yemeng Zhang ◽  
Min Zhu ◽  
Bohan Yang ◽  
Leibo Liu
Keyword(s):  
Random Number ◽  
Post Processing ◽  
Random Number Generators ◽  
Processing Algorithms

scholarly journals True-Randomness and Pseudo-Randomness in Ring Oscillator-Based True Random Number Generators

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
Nathalie Bochard ◽  
Florent Bernard ◽  
Viktor Fischer ◽  
Boyan Valtchanov
Keyword(s):  
Simulation Model ◽  
Mathematical Analysis ◽  
Random Number ◽  
Statistical Tests ◽  
System Security ◽  
Ring Oscillator ◽  
Post Processing ◽  
Random Number Generators ◽  
Entropy Reduction ◽  
The One

The paper deals with true random number generators employing oscillator rings, namely, with the one proposed by Sunar et al. in 2007 and enhanced by Wold and Tan in 2009. Our mathematical analysis shows that both architectures behave identically when composed of the same number of rings and ideal logic components. However, the reduction of the number of rings, as proposed by Wold and Tan, would inevitably cause the loss of entropy. Unfortunately, this entropy insufficiency is masked by the pseudo-randomness caused by XOR-ing clock signals having different frequencies. Our simulation model shows that the generator, using more than 18 ideal jitter-free rings having slightly different frequencies and producing only pseudo-randomness, will let the statistical tests pass. We conclude that a smaller number of rings reduce the security if the entropy reduction is not taken into account in post-processing. Moreover, the designer cannot avoid that some of rings will have the same frequency, which will cause another loss of entropy. In order to confirm this, we show how the attacker can reach a state where over 25% of the rings are locked and thus completely dependent. This effect can have disastrous consequences on the system security.

scholarly journals TRNGs from Pre-Formed ReRAM Arrays

Cryptography ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Bertrand Cambou ◽  
Donald Telesca ◽  
Sareh Assiri ◽  
Michael Garrett ◽  
Saloni Jain ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Random Access ◽  
Random Number Generators ◽  
Cryptographic Algorithms ◽  
Cryptographic Keys ◽  
Low Levels ◽  
Stochastic Properties ◽  
Pseudo Random Number Generator ◽  
Number Of Cells

Schemes generating cryptographic keys from arrays of pre-formed Resistive Random Access (ReRAM) cells, called memristors, can also be used for the design of fast true random number generators (TRNG’s) of exceptional quality, while consuming low levels of electric power. Natural randomness is formed in the large stochastic cell-to-cell variations in resistance values at low injected currents in the pre-formed range. The proposed TRNG scheme can be designed with three interconnected blocks: (i) a pseudo-random number generator that acts as an extended output function to generate a stream of addresses pointing randomly at the array of ReRAM cells; (ii) a method to read the resistance values of these cells with a low injected current, and to convert the values into a stream of random bits; and, if needed, (iii) a method to further enhance the randomness of this stream such as mathematical, Boolean, and cryptographic algorithms. The natural stochastic properties of the ReRAM cells in the pre-forming range, at low currents, have been analyzed and demonstrated by measuring a statistically significant number of cells. Various implementations of the TRNGs with ReRAM arrays are presented in this paper.

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