Artificial Neural Networks or Neural Networks (NN) is a machine learning technique composed of nodes called Artificial Neurons, just like the brain possesses. Such systems use Machine Learning to approximate highly dimensional functions and progressively learn through examples of training set data, or in our case a large password dump. They have shown initial promise to be effective at generating original yet representative password candidates. Advantages to NN's for password cracking are the low overhead for storing the final NN model, approximately 500kb, and the ability to continually learn over time through retraining or transfer learning. Resources Fast, Lean, and Accurate: Modeling Password Guessability Using Neural Networks (USENIX '16) https://www.usenix.org/system/files/conference/usenixsecurity16/sec16_paper_melicher.pdf https://github.com/cupslab/neural_network_cracking [[Home]] #advanced #concepts