share
research
∙
11/22/2017
MagNet and "Efficient Defenses Against Adversarial Attacks" are Not Robust to Adversarial Examples
MagNet and "Efficient Defenses..." were recently proposed as a defense t...
research
∙
06/26/2020
Proper Network Interpretability Helps Adversarial Robustness in Classification
Recent works have empirically shown that there exist adversarial example...
research
∙
10/25/2018
Evading classifiers in discrete domains with provable optimality guarantees
Security-critical applications such as malware, fraud, or spam detection...
research
∙
07/23/2020
Scalable Inference of Symbolic Adversarial Examples
We present a novel method for generating symbolic adversarial examples: ...
research
∙
04/03/2019
Interpreting Adversarial Examples by Activation Promotion and Suppression
It is widely known that convolutional neural networks (CNNs) are vulnera...
research
∙
07/03/2023
Interpretability and Transparency-Driven Detection and Transformation of Textual Adversarial Examples (IT-DT)
Transformer-based text classifiers like BERT, Roberta, T5, and GPT-3 hav...
research
∙
10/27/2018