Rapid Model Retraining for a New Attack Vector

摘要

A computer system that trains a neural network is described. During operation, the computer system may receive information specifying a new attack vector corresponding to fake audio content. In response, the computer system may generate a synthetic training dataset based at least in part on the new attack vector. Then, the computer system may access a predetermined neural network that classifies real audio content and fake audio content, where the predetermined neural network was training without synthetic audio content corresponding to the new attack vector. Next, the computer system may train the neural network based at least in part on the synthetic training dataset and the predetermined neural network, where the training of the neural network may include modifying predetermined weights associated with the predetermined neural network, and where a training time for training the neural network may be less than a training time for training the predetermined neural network.