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Entropy: measuring, estimating, and testing true randomness
The same module told visually, ready to present. Speaker notes carry the full explanation.
Foundations
Entropy: measuring true randomness
Randomness isn't assumed good or bad. It's measured, tested and conditioned
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Worst case, not average
Min-entropy is stricter than Shannon entropy
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The formula
Only the most likely outcome counts
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NIST SP 800-90B
How an entropy source is assessed
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Go deeper
Ten estimators, four kinds of weakness
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Hardware
True randomness versus pseudorandomness
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Conditioning
The von Neumann extractor
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Boot-time starvation
Keys generated before the pool fills
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Human randomness
Diceware: words beat symbols
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