Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
Authors: David Stutz, Matthias Hein, Bernt Schiele | Published: 2019-10-14 | Updated: 2020-06-30
ポイズニング
Eavesdrop the Composition Proportion of Training Labels in Federated Learning
Authors: Lixu Wang, Shichao Xu, Xiao Wang, Qi Zhu | Published: 2019-10-14 | Updated: 2019-10-27
Detecting AI Trojans Using Meta Neural Analysis
Authors: Xiaojun Xu, Qi Wang, Huichen Li, Nikita Borisov, Carl A. Gunter, Bo Li | Published: 2019-10-08 | Updated: 2020-10-01
Adversarial Examples for Cost-Sensitive Classifiers
Authors: Gavin S. Hartnett, Andrew J. Lohn, Alexander P. Sedlack | Published: 2019-10-04
BUZz: BUffer Zones for defending adversarial examples in image classification
Authors: Kaleel Mahmood, Phuong Ha Nguyen, Lam M. Nguyen, Thanh Nguyen, Marten van Dijk | Published: 2019-10-03 | Updated: 2020-06-16
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples
Authors: Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Emre Gursoy, Stacey Truex, Yanzhao Wu | Published: 2019-10-01
Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML
Authors: Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Minyi Hong, Una-May O'Reilly | Published: 2019-09-30 | Updated: 2020-06-17
GAMIN: An Adversarial Approach to Black-Box Model Inversion
Authors: Ulrich Aïvodji, Sébastien Gambs, Timon Ther | Published: 2019-09-26
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection
Authors: Aminollah Khormali, Ahmed Abusnaina, Songqing Chen, DaeHun Nyang, Aziz Mohaisen | Published: 2019-09-20
Defending Against Physically Realizable Attacks on Image Classification
Authors: Tong Wu, Liang Tong, Yevgeniy Vorobeychik | Published: 2019-09-20 | Updated: 2020-02-14