Phase-Coding Self-Testing Quantum Random Number Generator

2015 ◽  
Vol 32 (8) ◽  
pp. 080302 ◽  
Author(s):  
Xiao-Tian Song ◽  
Hong-Wei Li ◽  
Zhen-Qiang Yin ◽  
Wen-Ye Liang ◽  
Chun-Mei Zhang ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Phase Coding ◽  
Self Testing

scholarly journals Fast self-testing quantum random number generator based on homodyne detection

2020 ◽  
Vol 116 (26) ◽  
pp. 264004
Author(s):  
Davide Rusca ◽  
Hamid Tebyanian ◽  
Anthony Martin ◽  
Hugo Zbinden
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Homodyne Detection ◽  
Self Testing

Real-Time Self-Testing Quantum Random Number Generator with Non-classical States

2020 ◽  
Author(s):  
Thibault Michel ◽  
Jing Yan Haw ◽  
Davide G. Marangon ◽  
Oliver Thearle ◽  
Giuseppe Vallone ◽  
...  
Keyword(s):  
Real Time ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Self Testing ◽  
Classical States

scholarly journals Self-Testing Quantum Random Number Generator

2015 ◽  
Vol 114 (15) ◽  
Author(s):  
Tommaso Lunghi ◽  
Jonatan Bohr Brask ◽  
Charles Ci Wen Lim ◽  
Quentin Lavigne ◽  
Joseph Bowles ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Self Testing

scholarly journals Self-testing quantum random-number generator based on an energy bound

2019 ◽  
Vol 100 (6) ◽  
Author(s):  
Davide Rusca ◽  
Thomas van Himbeeck ◽  
Anthony Martin ◽  
Jonatan Bohr Brask ◽  
Weixu Shi ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Self Testing ◽  
Energy Bound

scholarly journals Hybrid quantum random number generator for cryptographic algorithms

2021 ◽  
pp. 103-118
Author(s):  
Maksim Iavich ◽  
Tamari Kuchukhidze ◽  
Giorgi Iashvili ◽  
Sergiy Gnatyuk
Keyword(s):  
Mathematical Model ◽  
Random Number ◽  
Random Number Generator ◽  
Random Numbers ◽  
Number Generator ◽  
Random Number Generators ◽  
Pseudo Random Number ◽  
Self Testing ◽  
High Level ◽  
Certification Method

The subject matter of the article is pseudo-random number generators. Random numbers play the important role in cryptography. Using not secure pseudo-random number generators is a very common weakness. It is also a fundamental resource in science and engineering. There are algorithmically generated numbers that are similar to random distributions but are not random, called pseudo-random number generators. In many cases the tasks to be solved are based on the unpredictability of random numbers, which cannot be guaranteed in the case of pseudo-random number generators, true randomness is required. In such situations, we use real random number generators whose source of randomness is unpredictable random events. Quantum Random Number Generators (QRNGs) generate real random numbers based on the inherent randomness of quantum measurements. The goal is to develop a mathematical model of the generator, which generates fast random numbers at a lower cost. At the same time, a high level of randomness is essential. Through quantum mechanics, we can obtain true numbers using the unpredictable behavior of a photon, which is the basis of many modern cryptographic protocols. It is essential to trust cryptographic random number generators to generate only true random numbers. This is why certification methods are needed which will check both the operation of the device and the quality of the random bits generated. The goal of the research is also to develop the model of a hybrid semi self-testing certification method for quantum random number generators (QRNG). The tasks to be solved are to create the mathematical model of a random number generator, which generates the fast random numbers at a lower cost. To create the mathematical model of a hybrid semi self-testing certification method for quantum random number generators. To integrate a hybrid semi self-testing certification method to the hybrid random number generator. the methods used are mathematical optimization and simulation. The following results were obtained: we present the improved hybrid quantum random number generator, which is based on QRNG, which uses the time of arrival of photons. The model of a hybrid semi self-testing certification method for quantum random number generators (QRNG) is offered in the paper. This method combines different types of certification approaches and is rather secure and efficient. Finally, the hybrid certification method is integrated into the model of the new quantum random number generator. Conclusions. The scientific novelty of the results obtained is as follows: 1. The hybrid quantum random number generator is offered, which is based on QRNG, which uses the time of the arrival of photons. It uses the simple version of the detectors with few requirements. The hybrid QRNG produces more than one random bit per the detection of each photon. It is rather efficient and has a high level of randomness. 2. The hybrid semi self-testing certification method for quantum random number generators (QRNG) is offered. The Self-testing, as well as device-independent quantum random number generation methods, are analyzed. The advantages and disadvantages of both methods are identified. Based on the result the hybrid method is offered. 3. The hybrid semi self-testing certification method for quantum random number generators is integrated into the offered model of the quantum random number generator. The paper analyzes its security and efficiency. The paper offers to use the new random number generator in the crypto-schemes.

Fuzzy Based Pseudo Random Number Generator used for Wireless Networks

2013 ◽  
Vol 16 (2) ◽  
pp. 210-216 ◽  
Author(s):  
Sattar B. Sadkhan ◽  
◽  
Sawsan K. Thamer ◽  
Najwan A. Hassan ◽  
◽  
...  
Keyword(s):  
Wireless Networks ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

0.4 mW, 0.27 pJ/bit true random number generator using jitter, metastability and current starved topology

2020 ◽  
Vol 14 (7) ◽  
pp. 1001-1011
Author(s):  
Dhirendra Kumar ◽  
Rahul Anand ◽  
Sajai Vir Singh ◽  
Prasanna Kumar Misra ◽  
Ashok Srivastava ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
True Random Number Generator

scholarly journals A High‐Speed True Random Number Generator Based on a Cu x Te 1− x Diffusive Memristor

2021 ◽  
pp. 2100062
Author(s):  
Kyung Seok Woo ◽  
Jaehyun Kim ◽  
Janguk Han ◽  
Jin Myung Choi ◽  
Woohyun Kim ◽  
...  
Keyword(s):  
High Speed ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
True Random Number Generator
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