ANALYZING TRUE AND PSEUDO-RANDOM NUMBER GENERATORS: IMPLICATIONS FOR CYBERSECURITY AND CYBER THREAT RESISTANCE

Abstract

Random number generation is a critical building block in computer science, underpinning applications in cryptography, simulations, secure communications, and statistical modeling. This paper presents a comprehensive overview of both true random number generators (TRNGs) and pseudo-random number generators (PRNGs)—two fundamentally different approaches to generating randomness. TRNGs rely on inherently unpredictable physical processes, such as thermal noise, radioactive decay, or quantum phenomena, to produce non-deterministic output. In contrast, PRNGs employ algorithmic methods that, while deterministic and reproducible, aim to simulate randomness from an initial seed value.