29 citations · 58 across the 4 of their papers we have counts for
3 papers · 1 filter
BOSH: An Efficient Meta Algorithm for Decision-based Attacks
Zhenxin Xiao, Puyudi Yang, Yuchen Jiang +2
Adversarial example generation becomes a viable method for evaluating the robustness of a machine learning model. In this paper, we consider hard-label black-box attacks (a.k.a. de…
ML-LOO: Detecting Adversarial Examples with Feature Attribution
Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh +2
Deep neural networks obtain state-of-the-art performance on a series of tasks. However, they are easily fooled by adding a small adversarial perturbation to input. The perturbation…
Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data
Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh +2
We present a probabilistic framework for studying adversarial attacks on discrete data. Based on this framework, we derive a perturbation-based method, Greedy Attack, and a scalabl…