Learning the Enigma with Recurrent Neural Networks

Understand

Recurrent neural networks (RNNs) represent the state of the art in translation, image captioning, and speech recognition.

• They are also capable of learning algorithmic tasks such as long addition, copying, and sorting from a set of training examples.
• We demonstrate that RNNs can learn decryption algorithms -- the mappings from plaintext to ciphertext -- for three polyalphabetic ciphers (Vigen\`ere, Autokey, and Enigma).
• Most notably, we demonstrate that an RNN with a 3000-unit Long Short-Term Memory (LSTM) cell can learn the decryption function of the Enigma machine.