How Entropy’s Math Protects Digital Security in the Biggest Vault
Foundations of Entropy and Information Theory Shannon’s entropy, defined as H = −Σ pᵢ log₂ pᵢ, measures the uncertainty inherent in a random variable—expressed in bits. This 1948 cornerstone of information theory established entropy as a precise tool for quantifying unpredictability, directly governing cryptographic strength. By assigning higher entropy to key distributions, systems ensure that cryptographic keys resist statistical guessing and brute-force attacks, forming the bedrock of secure key generation. The mathematical clarity of entropy provides a measurable guarantee:...