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Also known as: TRNG
Randomness generator that derives unpredictability from physical processes rather than deterministic algorithms.
DESCRIPTION
A true random number generator produces random values from physical phenomena like thermal noise, quantum effects, or chaotic systems. Unlike pseudo-random generators, TRNGs offer non-deterministic output crucial for cryptographic keys and security tokens. They often include conditioning components to extract uniform randomness. TRNGs are embedded in CPUs, security modules, and hardware tokens. Proper testing and health checks ensure adequate entropy and reliability.
ALTERNATIVE DEFINITIONS
Wikipedia
A hardware random number generator (true random number generator) generates random numbers from a physical process, rather than a computer program.
Contrasts TRNGs with software-based PRNGs using physical processes.
RFC 4086
Random numbers are vital for many cryptographic protocols; physical sources of randomness can be used to generate random data.
Emphasizes the importance of physical randomness sources in cryptography.
RELATED TERMS
Entropy Source Randomness Extraction Data Encryption Secure Key Generation Noise Entropy Seed Hardware Security Module Randomness Requirements
COMPETING TERMS
RELATIONS
- Broader: Random Number Generator
KNOWLEDGE AREAS
Data Security Infrastructure Software Engineering
TARGET AUDIENCE
Cybersecurity Engineer Security Architect Chief Information Security Officer Software Developer Cloud Architect
EXTERNAL SOURCES
- Wikipedia - Hardware random number generator
- IETF - Randomness requirements guidance
- NIST - Entropy source assessment recommendations
- Intel - CPU hardware RNG guidance
TOP QUESTIONS
What is a True Random Number Generator?
It’s a hardware-based generator that uses physical processes to produce non-deterministic random numbers.
Category: Definition
Why are TRNGs important for security?
They provide high-quality randomness for cryptographic keys, reducing predictability and attack surfaces compared to PRNGs.
Category: Relevancy
How do TRNGs differ from PRNGs?
TRNGs are non-deterministic and rely on physical phenomena; PRNGs are algorithmic and reproducible from seeds.
Category: Comparison
What are common TRNG physical sources?
Thermal noise, quantum effects, oscillator jitter, and radioactive decay are typical sources.
Category: Example
What risks exist with TRNGs?
Poor entropy sources, hardware faults, or manipulation can degrade randomness; health tests mitigate risk.
Category: Risks
How to validate TRNG quality?
Use continuous health tests, NIST SP 800-90B assessments, and statistical test suites like Dieharder.
Category: Testing
Can TRNGs be combined with PRNGs?
Yes, TRNGs seed PRNGs to ensure unpredictability while PRNGs provide speed and scalability.
Category: BestPractices
Where are TRNGs used in practice?
In HSMs, CPUs, secure boot, token generation, and cryptographic protocols needing strong randomness.
Category: UseCase
What is a hot topic around TRNGs?
Quantum TRNGs and on-chip RNG quality assurance are active areas of innovation.
Category: Topic