Adversarial attacks hidden in plain sight
Authors: Jan Philip Göpfert, André Artelt, Heiko Wersing, Barbara Hammer | Published: 2019-02-25 | Updated: 2020-04-26
敵対的学習
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence
Authors: Yi Han, David Hubczenko, Paul Montague, Olivier De Vel, Tamas Abraham, Benjamin I. P. Rubinstein, Christopher Leckie, Tansu Alpcan, Sarah Erfani | Published: 2019-02-25 | Updated: 2020-08-17
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
Authors: Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang | Published: 2019-02-23 | Updated: 2020-01-10
Quantifying Perceptual Distortion of Adversarial Examples
Authors: Matt Jordan, Naren Manoj, Surbhi Goel, Alexandros G. Dimakis | Published: 2019-02-21
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch
Authors: Gavin Weiguang Ding, Luyu Wang, Xiaomeng Jin | Published: 2019-02-20
A Little Is Enough: Circumventing Defenses For Distributed Learning
Authors: Moran Baruch, Gilad Baruch, Yoav Goldberg | Published: 2019-02-16
Model Compression with Adversarial Robustness: A Unified Optimization Framework
Authors: Shupeng Gui, Haotao Wang, Chen Yu, Haichuan Yang, Zhangyang Wang, Ji Liu | Published: 2019-02-10 | Updated: 2019-12-28
Is Spiking Secure? A Comparative Study on the Security Vulnerabilities of Spiking and Deep Neural Networks
Authors: Alberto Marchisio, Giorgio Nanfa, Faiq Khalid, Muhammad Abdullah Hanif, Maurizio Martina, Muhammad Shafique | Published: 2019-02-04 | Updated: 2020-05-18
A New Family of Neural Networks Provably Resistant to Adversarial Attacks
Authors: Rakshit Agrawal, Luca de Alfaro, David Helmbold | Published: 2019-02-01
Improving Adversarial Robustness via Promoting Ensemble Diversity
Authors: Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu | Published: 2019-01-25 | Updated: 2019-05-29