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Pseudorandom Number Generators | Computer Security

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As we’ve seen in the previous sections, cryptography often requires randomness. For example, symmetric keys are usually randomly-generated bits, and random IVs and nonces are required to build secure block cipher chaining modes. In cryptography, when we say “random,” we usually mean “random and unpredictable.” For example, flipping a biased coin that comes up heads 99% of the time is random, but you can predict a pattern–for a given coin toss, if you guess heads, it’s very likely you’re correct. A better source of randomness for cryptographic purposes would be flipping a fair coin, because the outcome is harder to predict than the outcome of the biased coin flip. Consider generating a random symmetric key: you would want to use outcomes of the fair coin to generate the key, because that makes it harder for the attacker to guess your key than if you had used outcomes of the biased coin to generate the key. We can formalize this concept of unpredictability by defining entropy, a measure

Pseudorandom Number Generators | Computer Security Skip to main content Menu Expand (external link) Document Search Copy Copied Computer Security 9. Pseudorandom Number Generators 9.1. Randomness and entropy As we’ve seen in the previous sections, cryptography often requires randomness. For example, symmetric keys are usually randomly-generated bits, and random IVs and nonces are required to build secure block cipher chaining modes. In cryptography, when we say “random,” we usually mean “random and unpredictable.” For example, flipping a biased coin that comes up heads 99% of the time is rando

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