Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
Authors: Nathan Inkawhich, Kevin J Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen | Published: 2020-04-29
敵対的攻撃検出
Minority Reports Defense: Defending Against Adversarial Patches
Authors: Michael McCoyd, Won Park, Steven Chen, Neil Shah, Ryan Roggenkemper, Minjune Hwang, Jason Xinyu Liu, David Wagner | Published: 2020-04-28
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks
Authors: Pranjal Awasthi, Natalie Frank, Mehryar Mohri | Published: 2020-04-28
Variational Encoder-based Reliable Classification
Authors: Chitresh Bhushan, Zhaoyuan Yang, Nurali Virani, Naresh Iyer | Published: 2020-02-19 | Updated: 2020-10-17
Indirect Adversarial Attacks via Poisoning Neighbors for Graph Convolutional Networks
Authors: Tsubasa Takahashi | Published: 2020-02-19
Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent
Authors: Pu Zhao, Pin-Yu Chen, Siyue Wang, Xue Lin | Published: 2020-02-18
Deflecting Adversarial Attacks
Authors: Yao Qin, Nicholas Frosst, Colin Raffel, Garrison Cottrell, Geoffrey Hinton | Published: 2020-02-18
On the Matrix-Free Generation of Adversarial Perturbations for Black-Box Attacks
Authors: Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Naoto Hayashi, Osamu Abe | Published: 2020-02-18
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets
Authors: Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma | Published: 2020-02-14
Challenges and Countermeasures for Adversarial Attacks on Deep Reinforcement Learning
Authors: Inaam Ilahi, Muhammad Usama, Junaid Qadir, Muhammad Umar Janjua, Ala Al-Fuqaha, Dinh Thai Hoang, Dusit Niyato | Published: 2020-01-27 | Updated: 2021-09-08