UNDERSTANDING RANDOMNESS IN COMPUTING: TRUE AND PSEUDO-RANDOM NUMBER GENERATORS
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Abstrak:
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.
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