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Random Number Generator

nounid 3752·updated May 9, 2026
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Random Number Generators (RNGs) used for cryptographic applications typically produce a sequence of zero and one bits that may be combined into sub-sequences or blocks of random numbers. There are two basic classes: deterministic and nondeterministic. A deterministic RNG consists of an algorithm that produces a sequence of bits from an initial value called a seed. A nondeterministic RNG produces output that is dependent on some unpredictable physical source that is outside human control.

polysemousMWE

Classifications

Entity Type

Capability78%llm-generatedllm:claude-haiku-4-5

Sensitivity

Restricted72%llm-generatedllm:claude-haiku-4-5

Information Class

65%llm-generatedllm:claude-haiku-4-5

Variants

acronym
RNG
plural
Random Number Generators
possessive
Random Number Generator's
pluralpossessive
Random Number Generators'

Framework definitions

NISTIR 7298: Glossary of Key Information Security Terms, Revision 22 sensesview framework →
§1
A process used to generate an unpredictable series of numbers. Each individual value is called random if each of the values in the total population of values has an equal probability of being selected.
§2 · sense_2_pending_review
Random Number Generators (RNGs) used for cryptographic applications typically produce a sequence of zero and one bits that may be combined into sub-sequences or blocks of random numbers. There are two basic classes: deterministic and nondeterministic. A deterministic RNG consists of an algorithm that produces a sequence of bits from an initial value called a seed. A nondeterministic RNG produces output that is dependent on some unpredictable physical source that is outside human control.
CNSSI-4009 (Glossary of Information Assurance Terms)1 senseview framework →
§1
A process used to generate an unpredictable series of numbers. Each individual value is called random if each of the values in the total population of values has an equal probability of being selected.
FIPS PUB 140-21 senseview framework →
§1
Random Number Generators (RNGs) used for cryptographic applications typically produce a sequence of zero and one bits that may be combined into sub-sequences or blocks of random numbers. There are two basic classes: deterministic and nondeterministic. A deterministic RNG consists of an algorithm that produces a sequence of bits from an initial value called a seed. A nondeterministic RNG produces output that is dependent on some unpredictable physical source that is outside human control.

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