True Random Number Generators for Cryptography

Dhananjay S. Deshpande, Aman Kumar Nirala, Ayodeji Olalekan Salau

Mario Stipčević

Kyungroul Lee, Sun‐Young Lee, Changho Seo +1 more

The key point of cryptography is cryptographic algorithms and keys. The random number generator is used to generate seeds and keys randomly in many cryptographic systems. For this reason, it is essential to use keys to encrypt and decrypt the transferring information, and the security of these keys is closely related to the security of 5G network. We propose a true random number generator (TRNG) method in this paper, and are using visible spectrum for noise source. We consider that if the cryptography system utilizes data of visible spectrum using the proposed TRNG, and the TRNG generates random numbers with high entropy.

Mario Stipčević, Çetin Kaya Koç

Andrzej Gnatowski, Jarosław Rudy, Teodor Niżyński +1 more

Random number generation is fundamental for many modern applications including cryptography, simulations and machine learning. Traditional pseudo-random numbers may offer statistical unpredictability, but are ultimately deterministic. On the other hand, True Random Number Generation (TRNG) offers true randomness. One way of obtaining such randomness are quantum systems, including quantum computers. As such the use of quantum computers for TRNG has received considerable attention in recent years. However, existing studies almost exclusively consider IBM quantum computers, often stop at using simulations and usually test only a handful of different TRNG quantum circuits. In this paper, we address those issues by presenting a study of TRNG circuits on Odra 5 a real-life quantum computer installed at Wrocław University of Science and Technology. It is also the first study to utilize the IQM superconducting architecture. Since Odra 5 is available on-premises it allows for much more comprehensive study of various TRNG circuits. In particular, we consider 5 types of TRNG circuits with 105 circuit subvariants in total. Each circuit is used to generate 1 million bits. We then perform an analysis of the quality of the obtained random sequences using the NIST SP 800-22 and NIST SP 800-90B test suites. We also provide a comprehensive review of existing literature on quantum computer-based TRNGs.

Vaishnavi Kumar, Padmapriya Praveenkumar

Random numbers are used in various domains, including quantum communication and cryptography applications such as key generation and authentication. Quantum mechanics has the intrinsic ability to generate truly random numbers, making it an ideal alternative for scientific applications that require randomness. Quantum wireless communication is proposed as a new means of communication that is safe, secure, and efficient. The simplicity of our source rotation gate, combined with its independently verifiable solitary unpredictability, is essential to obtain quantum random number generators without spending any money. In this chapter, we explore and study the 24-qubit random number. The worst-case entropy value for such randomly produced integers is 0.999445, with the min-entropy of such numbers being 0.0008. Additionally, steering restart tests were used to validate later verification of true randomness, and the statistical characteristics of the True Random Number Generation (TRNG) were assessed using an autocorrelation study and the statistical test suites.