Bayesian inference in codebreaking

Bayesian inference in codebreaking involves updating our beliefs about a secret message as we gather clues. Starting with an initial guess, or prior probability, we analyze new evidence—such as patterns or frequency of symbols—to refine our estimate of the correct message. Each new piece of information adjusts the likelihood of different possibilities, leading us to a more probable solution. Essentially, it’s like piecing together a puzzle: we use initial assumptions and continuously revise them based on incoming clues, ultimately converging on the most likely interpretation of the secret code.