On the Intriguing Connections of Regularization, Input Gradients and Transferability of Evasion and Poisoning Attacks

Transferability captures the ability of an attack against a machine-learning model to be effective against a different, potentially unknown, model. Studying transferability of attacks has gained interest in the last years due to the deployment of cyber-attack detection services based on machine learning. For these applications of machine ...More