We propose a novel approach to deciphering short monoalphabetic ciphers that combines both character-level and word-level language models. We formulate decipherment as tree search, and use Monte Carlo Tree Search (MCTS) as a fast alternative to beam search. Our experiments show a significant improvement over the state of the art on a benchmark suite of short ciphers. Our approach can also handle ciphers without spaces and ciphers with noise, which allows us to explore its applications to unsupervised transliteration and deniable encryption.
REF propose a novel approach for solving mono-alphabetic substitution ciphers which combines character-level and word-level language model.
Solving Substitution Ciphers with Combined Language Models
COLING
Computer Science