Entropy source

As explained in Hacking Cryptography

A physical or computational process that supplies uncertain values from which random output can be derived.

An entropy source is the physical process sampled by a true random number generator (TRNG) to produce uncertain values. Its output may be biased or degraded, so production systems commonly apply randomness extraction before using it. section 2.2.1

Treat an entropy source as an engineered security boundary:

• Ground its generation rate and entropy in a physical model that can withstand skeptical review. section 2.2.1
• Expose raw output so a health checker can compare observed bits with the model’s predictions. section 2.2.1
• Shut down access when health checks detect malfunction, and defend against power-noise injection or malicious hosts. section 2.2.1

Practical failure modes

Zener-noise and ring-oscillator TRNGs illustrate why a physical model matters. Intel’s RDRAND hides the circuit between the entropy source and reported output, while USB TRNGs can be modified by a malicious host to produce permanently predictable bits. section 2.2.1

Figure 2.4 TRNGs sample physical phenomena to generate random numbers.

Shows how TRNGs sample physical phenomena to generate random numbers. section 2.2.1

How Hacking Cryptography covers it

How deep it goes

Explains physical modeling, raw-output inspection, extraction, health checks, and attacks, but does not derive circuit designs.

Examples

Uses Zener noise, ring oscillators, Intel RDRAND, USB TRNGs, and ambient-temperature bias as examples.

What you can do after

Evaluate TRNG designs by checking physical justification, raw-output visibility, health shutdown, extraction, and resistance to physical or host attacks.

How it connects

Connects entropy sources with TRNGs, randomness extractors, health checkers, physical models, and power-supply noise injection.

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Also explained in

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  Real-World CryptographyAn entropy source is a physical or computational process that supplies unpredictable or partially unpredictable input for random-data generation.

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Related concepts

• crypto/rand packageused by · The crypto/rand package is Go’s standard-library package for generating cryptographically secure random data from system-provided entropy sources.
• cryptographically secure random number generatorused by · A cryptographically secure random number generator produces computationally unpredictable values while resisting prediction and recovery of its internal state by feasible adversaries.
• pseudo-random number generatoruses · A pseudorandom number generator is a deterministic computational process that uses an initial seed or internal state to produce a sequence with random-like statistical properties.
• operating systemused by · An operating system is system software that manages computer hardware and provides services and interfaces for application programs.
• true random number generatorused by · A true random number generator produces unpredictable values by sampling nondeterministic physical phenomena rather than relying solely on deterministic algorithms.

This explainer was generated by Manning's knowledge graph from the text of Hacking Cryptography. The section links point to the parts of the book it draws on.