 Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve
Adversarial RobustnessComputer Vision and Pattern Recognition (CVPR), 2020 |
 Randomization matters. How to defend against strong adversarial attacksInternational Conference on Machine Learning (ICML), 2020 |
 DLA: Dense-Layer-Analysis for Adversarial Example DetectionEuropean Symposium on Security and Privacy (EuroS&P), 2019 |
 Moving Target Defense for Deep Visual Sensing against Adversarial
ExamplesACM International Conference on Embedded Networked Sensor Systems (SenSys), 2019 |
 Adversarial Perturbations Against Real-Time Video Classification SystemsNetwork and Distributed System Security Symposium (NDSS), 2018 |
 PixelDefend: Leveraging Generative Models to Understand and Defend
against Adversarial ExamplesInternational Conference on Learning Representations (ICLR), 2017 |
