GENERATING RANDOM PASS-PHRASES USING WORD-LEVEL RECURRENT NEURAL NETWORKS

摘要

Systems and methods are provided for generating random pass-phrases using word-level recurrent neural networks (RNNs). A pass-phrase includes a random sequence of words selected from a text corpus used to train an RNN model. The pass-phrase generation process utilizes a seed phrase obtained from the training text corpus, and a random bit string. The seed phrase is processed by the RNN model to generate a set of predicted words and associated likelihood values that the predicted words are a next word following the seed phrase. The prediction results are encoded into a binary tree which is traversed using a portion of the random bit string to identify a word at a leaf node which matches the portion of the random bit string. The identified word is selected as a constituent of the random pass-phrase, and the process is repeated until the random bit stream is exhausted.