A lightweight true random number generator using beta radiation for IoT applications

Park, Kyung-Hwan; Park, Seongmo; Choi, Byoung Gun; Kang, Taewook; Kim, Jong Bum; Kim, Young‐Hee; Jin, Hongzhou

doi:10.4218/etrij.2020-0119

Cited by 9 publications

(4 citation statements)

References 10 publications

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“…Thus, it is natural to try to use a property of quantum mechanics to generate completely random sequences of numbers. There exist methods exploiting such quantum processes as nuclear decay [78][79][80], or photons hitting a translucent mirror, e.g. id Quantique RNG [81].…”

Section: Private Randomness Generationmentioning

confidence: 99%

Quantum security and theory of decoherence

Mironowicz

2022

New J. Phys.

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We sketch a relation between two crucial, yet independent, fields in quantum information research, viz. quantum decoherence and quantum cryptography. We investigate here how the standard cryptographic assumption of shielded laboratory, stating that data generated by a secure quantum device remain private unless explicitly published, is disturbed by the einselection mechanism of quantum Darwinism explaining the measurement process by interaction with the external environment. We illustrate the idea with a paradigmatic example of a quantum random number generator compromised by an analog of the Van Eck phreaking. In particular, we derive a trade-off relation between eavesdropper's guessing probability Pguess and the collective decoherence factor Γ of the simple form Pguess + Γ ≥ 1.

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Section: Private Randomness Generationmentioning

confidence: 99%

Quantum security and theory of decoherence

Mironowicz

2022

New J. Phys.

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“…However, recently a PRNG was developed based on the use of beta radiations enabled by integrated circuits (ICs) suitably designed to detect the very low energy of these radiations [49,50]. This generator, although with a low number of bits, has shown a relatively simple structure, low-cost and small volume, passing the National Institute of Standards and Technology (NIST) test [48].…”

Section: Pseudo-random Numbers Generators and Cryptography Securitymentioning

confidence: 99%

Counter-Interception and Counter-Exploitation Features of Noise Radar Technology

et al. 2021

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In defense applications, the main features of radars are the Low Probability of Intercept (LPI) and the Low Probability of Exploitation (LPE). The counterpart uses more and more capable intercept receivers and signal processors thanks to the ongoing technological progress. Noise Radar Technology (NRT) is probably a very effective answer to the increasing demand for operational LPI/LPE radars. The design and selection of the radiated waveforms, while respecting the prescribed spectrum occupancy, has to comply with the contrasting requirements of LPI/LPE and of a favorable shape of the ambiguity function. Information theory seems to be a “technologically agnostic” tool to attempt to quantify the LPI/LPE capability of noise waveforms with little, or absent, a priori knowledge of the means and the strategies used by the counterpart. An information theoretical analysis can lead to practical results in the design and selection of NRT waveforms.

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“…Therefore, it seems natural to utilize them as a source of random numbers in the sense of a quantum random number generator (QRNG) (Herrero-Collantes and Garcia-Escartin, 2017). Such QRNGs have already been realized with different quantum systems, for example using nuclear decay (Park et al, 2020) or optical devices (Leone et al, 2020).…”

Section: Quantum Rngsmentioning

confidence: 99%

On the effects of biased quantum random numbers on the initialization of artificial neural networks

Heese¹,

Sascha²,

Franken³

et al. 2021

Preprint

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Recent advances in practical quantum computing have led to a variety of cloud-based quantum computing platforms that allow researchers to evaluate their algorithms on noisy intermediate-scale quantum (NISQ) devices. A common property of quantum computers is that they exhibit instances of true randomness as opposed to pseudo-randomness obtained from classical systems. Investigating the effects of such true quantum randomness in the context of machine learning is appealing, and recent results vaguely suggest that benefits can indeed be achieved from the use of quantum random numbers. To shed some more light on this topic, we empirically study the effects of hardware-biased quantum random numbers on the initialization of artificial neural network weights in numerical experiments. We find no statistically significant difference in comparison with unbiased quantum random numbers as well as biased and unbiased random numbers from a classical pseudo-random number generator. The quantum random numbers for our experiments are obtained from real quantum hardware.

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A lightweight true random number generator using beta radiation for IoT applications

Cited by 9 publications

References 10 publications

Quantum security and theory of decoherence

Quantum security and theory of decoherence

Counter-Interception and Counter-Exploitation Features of Noise Radar Technology

On the effects of biased quantum random numbers on the initialization of artificial neural networks

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