1.8k citations · 2.4k across the 86 of their papers we have counts for
11 papers · 2 filters
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification
Qi Lei, Lingfei Wu, Pin-Yu Chen +3
Adversarial examples are carefully constructed modifications to an input that completely change the output of a classifier but are imperceptible to humans. Despite these successful…
Efficient Neural Network Robustness Certification with General Activation Functions
Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen +2
Finding minimum distortion of adversarial examples and thus certifying robustness in neural network classifiers for given data points is known to be a challenging problem. Neverthe…
On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen +3
CLEVER (Cross-Lipschitz Extreme Value for nEtwork Robustness) is an Extreme Value Theory (EVT) based robustness score for large-scale deep neural networks (DNNs). In this paper, we…
Characterizing Audio Adversarial Examples Using Temporal Dependency
Zhuolin Yang, Bo Li, Pin-Yu Chen +1
Recent studies have highlighted adversarial examples as a ubiquitous threat to different neural network models and many downstream applications. Nonetheless, as unique data propert…
Structured Adversarial Attack: Towards General Implementation and Better Interpretability
Kaidi Xu, Sijia Liu, Pu Zhao +6
When generating adversarial examples to attack deep neural networks (DNNs), Lp norm of the added perturbation is usually used to measure the similarity between original image and a…
Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach
Minhao Cheng, Thong Le, Pin-Yu Chen +3
We study the problem of attacking a machine learning model in the hard-label black-box setting, where no model information is revealed except that the attacker can make queries to…