Journals | Security and Safety
#NewArticle #OpenAccess

"A survey of random number generator: Approaches, tests, novel applications in block-chain and AI driven industrial networks"
✍️Xinping Guan et al. from Waseda University, Fukuoka, Japan
Read more ➡️ https://bit.ly/3MK15gC

#TRNG #Block-chain #MachineLearning

#TRNG #RNG #security #TrueRandomNumbers

Apparently Western-minds don't undstand the difference between *random* and *arbitrary+unpredictable*??

Arbitrary-unpredictable ISN'T true-random..

Nearly-all of the TRNG devices I've just read-about have feedback-systems,
which use A PSEUDO-RANDOM generator or other algorithm, some using elliptic-curve calculations,

.. they're using the true-random-number as the seed/source,
so that they can produce many-times-more *unpredictable* bits..

but .. unpredictable *isn't identical-with* random.

It's functionally-similar,

from normal-user's perspective, & from *normal* security's perspective, they're "the same",
but .. true-random has to be NOT put through something like the Mersene-Twister, or whatever, to multiply the number of unpredictable-bits:

it needs to be left-alone..

( mind-you, all the use-cases being served *are* being served well, with these arbitrary-unpredictable sources, in industry..

it's only in science that I'd, in some use-cases, banish such fakery )

Think of it this-way:

True-random's quantum, & arbitrary-unpredictable's classical.

Sometimes you NEED quantum-behavior, see?

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Программный генератор случайных числовых последовательностей на RISC-V с использованием PUF в DRAM

Мы продолжаем рассказывать о проектах Зимней школы RISC-V , организованной

https://habr.com/ru/companies/yadro/articles/909902/

#trng #riscv #динамическая_память

This article describes how to generate random numbers using the SCE5 encryption engine mounted on the RA4M1.

Exploring the Hardware Random Number Generator of Arduino R4 MINIMA - https://blog.jetzou.com/en/post/202404/arduino-r4-minima-use-sce5-trng/

#arduino #trng

S. Su et al., "A Closer Look at the Chaotic Ring Oscillators based TRNG Design"¹

[...]A digital FIRO-/GARO-based TRNG with high throughput and high entropy rate was introduced by Jovan Dj. Golić (TC’06). However, the fact that periodic oscillation is a main failure of FIRO-/GARO-based TRNGs is noticed in the paper (Markus Dichtl, ePrint’15). We verify this problem and estimate the consequential entropy loss using Lyapunov exponents and the test suite of the NIST SP 800-90B standard. To address the problem of periodic oscillations, we propose several implementation guidelines based on a gate-level model, a design methodology to build a reliable GARO-based TRNG, and an online test to improve the robustness of FIRO-/GARO-based TRNGs. The gate-level implementation guidelines illustrate the causes of periodic oscillations, which are verified by actual implementation and bifurcation diagram. Based on the design methodology, a suitable feedback polynomial can be selected by evaluating the feedback polynomials. The analysis and understanding of periodic oscillation and FIRO-/GARO-based TRNGs are deepened by delay adjustment. A TRNG with the selected feedback polynomial may occasionally enter periodic oscillations, due to active attacks and the delay inconstancy of implementations. This inconstancy might be caused by self-heating, temperature and voltage fluctuation, and the process variation among different silicon chips. Thus, an online test module, as one indispensable component of TRNGs, is proposed to detect periodic oscillations. The detected periodic oscillation can be eliminated by adjusting feedback polynomial or delays to improve the robustness. The online test module is composed of a lightweight and responsive detector with a high detection rate, outperforming the existing detector design and statistical tests. The areas, power consumptions and frequencies are evaluated based on the ASIC implementations of a GARO, the sampling circuit and the online test module. [...]
#IACR #ResearchPapers #TRNG
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¹ https://eprint.iacr.org/2023/040

Dice Rolls From the Beginning of Time

Generating random numbers might seem like a trivial task, that is until the numbers need to be truly random for cryptography or security reasons. When that's the case, it turns out that these numbers are really "pseudo-random" and follow a predictable pattern. Devices that can produce truly random numbers often do it by sampling random events in the real world rather than relying on a computer to do it directly, like this machine which simulates a dice roll by looking at the cosmic microwave background radiation.

The cosmic microwave background radiation exists in the infrared at the farthest edges of the observable universe as a remnant of the big bang. It's an excellent source of randomness, but tapping into it poses a bit of a challenge. For this build, [iSax] is using an old Soviet-era Geiger tube to detect the appropriate signal, and a Nixie tube to display the dice roll. After the device detects two particles from the Big Bang, the device measures the amount of time that passed between the detection of both particles and uses this number to calculate the dice roll.

While it takes a little bit longer to roll this dice than a traditional one since it has to wait to detect the right kind of particles, if you really need the randomness it can't be beat. It certainly works as dice, but we can also see some use for generating truly random numbers for other applications as well. For some other sources of random inspiration be sure to check out our own [Voja Antonic]'s deep dive into truly random number generation.

#science #nixietube #prng #randomnumbergenerator #trng