1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World
Weiran Lin, Keane Lucas, Neo Eyal +3
Machine-learning models are known to be vulnerable to evasion attacks that perturb model inputs to induce misclassifications. In this work, we identify real-world scenarios where t…
cs.LG2021★ 1 cited
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks
Weiran Lin, Keane Lucas, Lujo Bauer +2
We propose new, more efficient targeted white-box attacks against deep neural networks. Our attacks better align with the attacker's goal: (1) tricking a model to assign higher pro…