TextDecepter: Hard Label Black Box Attack on Text Classifiers
Authors: Sachin Saxena | Published: 2020-08-16 | Updated: 2020-12-28
敵対的訓練
Learning to Learn from Mistakes: Robust Optimization for Adversarial Noise
Authors: Alex Serban, Erik Poll, Joost Visser | Published: 2020-08-12
Evaluation of Adversarial Training on Different Types of Neural Networks in Deep Learning-based IDSs
Authors: Rana Abou Khamis, Ashraf Matrawy | Published: 2020-07-08
On the transferability of adversarial examples between convex and 01 loss models
Authors: Yunzhe Xue, Meiyan Xie, Usman Roshan | Published: 2020-06-14 | Updated: 2020-07-29
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data
Authors: Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang | Published: 2020-05-11 | Updated: 2020-11-10
Towards Robustness against Unsuspicious Adversarial Examples
Authors: Liang Tong, Minzhe Guo, Atul Prakash, Yevgeniy Vorobeychik | Published: 2020-05-08 | Updated: 2020-10-08
Revisiting Ensembles in an Adversarial Context: Improving Natural Accuracy
Authors: Aditya Saligrama, Guillaume Leclerc | Published: 2020-02-26
Gödel’s Sentence Is An Adversarial Example But Unsolvable
Authors: Xiaodong Qi, Lansheng Han | Published: 2020-02-25
HYDRA: Pruning Adversarially Robust Neural Networks
Authors: Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana | Published: 2020-02-24 | Updated: 2020-11-10
Non-Intrusive Detection of Adversarial Deep Learning Attacks via Observer Networks
Authors: Kirthi Shankar Sivamani, Rajeev Sahay, Aly El Gamal | Published: 2020-02-22