Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning
Authors: Christopher Frederickson, Michael Moore, Glenn Dawson, Robi Polikar | Published: 2018-02-20
Adversarial Example Detection
The Robust Manifold Defense: Adversarial Training using Generative Models
Authors: Ajil Jalal, Andrew Ilyas, Constantinos Daskalakis, Alexandros G. Dimakis | Published: 2017-12-26 | Updated: 2019-07-10
Attacking the Madry Defense Model with $L_1$-based Adversarial Examples
Authors: Yash Sharma, Pin-Yu Chen | Published: 2017-10-30 | Updated: 2018-07-27
One pixel attack for fooling deep neural networks
Authors: Jiawei Su, Danilo Vasconcellos Vargas, Sakurai Kouichi | Published: 2017-10-24 | Updated: 2019-10-17
Boosting Adversarial Attacks with Momentum
Authors: Yinpeng Dong, Fangzhou Liao, Tianyu Pang, Hang Su, Jun Zhu, Xiaolin Hu, Jianguo Li | Published: 2017-10-17 | Updated: 2018-03-22
Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification
Authors: Xiaoyu Cao, Neil Zhenqiang Gong | Published: 2017-09-17 | Updated: 2019-12-31
NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles
Authors: Jiajun Lu, Hussein Sibai, Evan Fabry, David Forsyth | Published: 2017-07-12
MagNet: a Two-Pronged Defense against Adversarial Examples
Authors: Dongyu Meng, Hao Chen | Published: 2017-05-25 | Updated: 2017-09-11
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction
Authors: Bin Liang, Hongcheng Li, Miaoqiang Su, Xirong Li, Wenchang Shi, Xiaofeng Wang | Published: 2017-05-23 | Updated: 2019-01-09
Universal Adversarial Perturbations Against Semantic Image Segmentation
Authors: Jan Hendrik Metzen, Mummadi Chaithanya Kumar, Thomas Brox, Volker Fischer | Published: 2017-04-19 | Updated: 2017-07-31