How deeply does Real-World Cryptography cover randomness extractor?

Explains imperfect inputs and a hash-and-XOR pattern, but stops short of detailed extractor algorithms or operating-system methods.

Randomness extractor

As explained in Real-World Cryptography

A randomness extractor is a procedure that combines and transforms imperfect random inputs into output with improved randomness properties.

A randomness extractor cleans imperfect noise before cryptographic use. Entropy sources may be biased, correlated, insufficient, predictable, or influenced by outside factors, so one source is not automatically trustworthy. section 8.1

A practical extraction pattern is:

Gather noise from several sources, such as physical phenomena measured by hardware random number generators. section 8.1
Hash the different inputs to transform their raw noise. section 8.1
XOR the resulting digests together before using the output for cryptographic applications. section 8.1

Combining noisy measurements

Suppose one sensor produces a zero slightly more often than a one, while successive bits from another sensor are correlated. Hash both inputs and XOR the digests to gather and clean their noise. Extraction can be slow, however, making high-volume random-number generation a possible bottleneck. section 8.1

How Real-World Cryptography covers it

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Also explained in

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Hacking CryptographyA randomness extractor is an algorithm that converts a weakly random source into output with stronger and more uniform randomness properties.

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Related concepts

hash functionuses · A hash function deterministically maps input data to a value in a bounded output range, commonly for indexing, lookup, comparison, or integrity checking.
biasaddresses · Bias is a systematic deviation or tendency in data, measurements, estimates, judgments, or outputs that skews them relative to a relevant target or impartial baseline.
logical XORuses · Logical XOR is a binary operation that produces true when exactly one operand is true and false when both operands have the same truth value.

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