Review

A survey of random number generator: Approaches, tests, novel applications in block-chain and AI driven industrial networks

Graduate School of Information, Production and Systems, Waseda University, Fukuoka, 808-0135, Japan

^* Corresponding authors (email: This email address is being protected from spambots. You need JavaScript enabled to view it. (Qianqian Pan); email: This email address is being protected from spambots. You need JavaScript enabled to view it. (Jun Wu))

Received: 6 April 2025
Revised: 25 September 2025
Accepted: 28 October 2025

Abstract

True Random Number Generators (TRNGs) are essential components in industrial systems and security-critical applications, providing non-deterministic randomness based on physical phenomena such as electronic noise, quantum effects, and biological processes. Unlike Pseudo-Random Number Generators (PRNGs), TRNGs offer stronger unpredictability, making them crucial in areas such as industrial control systems (ICS), secure communications, and block-chain protocols. This survey provides a comprehensive review of TRNG technologies. It covers various types of TRNGs and their physical principles, traces their historical development from early hardware to modern implementations, and examines widely used statistical and visual analysis methods for evaluating randomness. We also discuss key challenges in TRNG development, including entropy source reliability, hardware limitations, and scalability for real-world deployment. Furthermore, we explore TRNG applications in block-chain systems, where they support tamper-resistant operations such as consensus, smart contracts, and device authentication. We also highlight the growing integration of TRNGs with machine learning techniques, both to improve randomness generation and to monitor and analyze TRNG output. Overall, this review aims to provide researchers and practitioners with a clear and structured understanding of TRNGs, emphasizing their importance in modern digital and industrial environments.