Analyse de texte et cryptanalyse

Text analysis studies the measurable patterns inside written language: letter counts, character distribution, repeated words, common pairs and triples, spacing, symbol variety, and other statistical signals. In cryptography, these patterns are especially useful because many classical ciphers hide the letters but still preserve traces of the original language.

Cryptanalysis uses those traces to make educated guesses. A high-frequency symbol may point to a common plaintext letter, repeated groups may reveal a keyword or phrase, and unusual entropy can suggest whether a message is natural language, encoded data, or encrypted text.

Frequency analysis is the natural starting point for most manual cryptanalysis. It shows which letters, symbols, words, bigrams, and trigrams appear most often, then compares those results with expected language profiles. For simple substitution systems, this can quickly reveal likely mappings between ciphertext and plaintext.

For Caesar-style shifts, a strong frequency peak can often suggest the key directly. For substitution and affine ciphers, frequency tables provide candidate letter mappings. For Vigenere and other polyalphabetic ciphers, frequency analysis becomes more useful when combined with key-length methods such as the Index of Coincidence and repeated n-gram analysis.

Different questions call for different measurements. Letter frequency helps identify language and attack monoalphabetic substitution. N-gram analysis highlights repeated fragments and common letter combinations. The Index of Coincidence helps distinguish random-looking text from language-like text and can estimate key lengths in some polyalphabetic ciphers.

Entropy analysis measures how predictable or random a text appears, while word pattern tools help match repeated-letter shapes such as ATTACK, PEOPLE, or LETTER against possible dictionary words. Together, these methods turn an unknown text into a set of practical clues.

Statistical methods work best when the text is long enough and the cipher preserves some structure from the original language. Short messages, mixed alphabets, heavy punctuation changes, transposition, homophonic substitution, or deliberate padding can make the results harder to interpret.

Modern encryption algorithms are designed to remove useful language patterns, so these tools are intended for learning, historical ciphers, puzzle solving, text diagnostics, and exploratory analysis rather than attacking secure contemporary cryptography.