A Survey of Black-Box Adversarial Attacks on Computer Vision Models
Authors: Siddhant Bhambri, Sumanyu Muku, Avinash Tulasi, Arun Balaji Buduru | Published: 2019-12-03 | Updated: 2020-02-07
ポイズニング
Data Poisoning Attacks on Neighborhood-based Recommender Systems
Authors: Liang Chen, Yangjun Xu, Fenfang Xie, Min Huang, Zibin Zheng | Published: 2019-12-01
An Adaptive View of Adversarial Robustness from Test-time Smoothing Defense
Authors: Chao Tang, Yifei Fan, Anthony Yezzi | Published: 2019-11-26
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning
Authors: Minghong Fang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong | Published: 2019-11-26 | Updated: 2021-11-21
Adversarial Learning of Privacy-Preserving and Task-Oriented Representations
Authors: Taihong Xiao, Yi-Hsuan Tsai, Kihyuk Sohn, Manmohan Chandraker, Ming-Hsuan Yang | Published: 2019-11-22
Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic
Authors: Zhen Xiang, David J. Miller, Hang Wang, George Kesidis | Published: 2019-11-18 | Updated: 2020-04-06
Adversarial Examples in Modern Machine Learning: A Review
Authors: Rey Reza Wiyatno, Anqi Xu, Ousmane Dia, Archy de Berker | Published: 2019-11-13 | Updated: 2019-11-15
A Tale of Evil Twins: Adversarial Inputs versus Poisoned Models
Authors: Ren Pang, Hua Shen, Xinyang Zhang, Shouling Ji, Yevgeniy Vorobeychik, Xiapu Luo, Alex Liu, Ting Wang | Published: 2019-11-05 | Updated: 2020-11-21
Online Robustness Training for Deep Reinforcement Learning
Authors: Marc Fischer, Matthew Mirman, Steven Stalder, Martin Vechev | Published: 2019-11-03 | Updated: 2019-11-22
Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization
Authors: Rana Abou Khamis, Omair Shafiq, Ashraf Matrawy | Published: 2019-10-30