On the Robustness of Dataset Inference
Authors: Sebastian Szyller, Rui Zhang, Jian Liu, N. Asokan | Published: 2022-10-24 | Updated: 2023-06-19
敵対的訓練
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy
Authors: Raphael Olivier, Bhiksha Raj | Published: 2022-07-08 | Updated: 2023-08-10
Robust Upper Bounds for Adversarial Training
Authors: Dimitris Bertsimas, Xavier Boix, Kimberly Villalobos Carballo, Dick den Hertog | Published: 2021-12-17 | Updated: 2023-04-06
Addressing Adversarial Machine Learning Attacks in Smart Healthcare Perspectives
Authors: Arawinkumaar Selvakkumar, Shantanu Pal, Zahra Jadidi | Published: 2021-12-16
Model Stealing Attacks Against Inductive Graph Neural Networks
Authors: Yun Shen, Xinlei He, Yufei Han, Yang Zhang | Published: 2021-12-15
Robustifying automatic speech recognition by extracting slowly varying features
Authors: Matías Pizarro, Dorothea Kolossa, Asja Fischer | Published: 2021-12-14 | Updated: 2024-11-06
CAPTIVE: Constrained Adversarial Perturbations to Thwart IC Reverse Engineering
Authors: Amir Hosein Afandizadeh Zargari, Marzieh AshrafiAmiri, Minjun Seo, Sai Manoj Pudukotai Dinakarrao, Mohammed E. Fouda, Fadi Kurdahi | Published: 2021-10-21
Evaluating Deep Learning Models and Adversarial Attacks on Accelerometer-Based Gesture Authentication
Authors: Elliu Huang, Fabio Di Troia, Mark Stamp | Published: 2021-10-03
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart
Authors: Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu | Published: 2021-05-31 | Updated: 2022-03-31
Robustifying $\ell_\infty$ Adversarial Training to the Union of Perturbation Models
Authors: Ameya D. Patil, Michael Tuttle, Alexander G. Schwing, Naresh R. Shanbhag | Published: 2021-05-31 | Updated: 2021-06-11