Holistic Adversarial Robustness of Deep Learning Models
Authors: Pin-Yu Chen, Sijia Liu | Published: 2022-02-15 | Updated: 2023-01-05
ポイズニング
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation
Authors: Wenxiao Wang, Alexander Levine, Soheil Feizi | Published: 2022-02-05 | Updated: 2022-07-14
Linear Model Against Malicious Adversaries with Local Differential Privacy
Authors: Guanhong Miao, A. Adam Ding, Samuel S. Wu | Published: 2022-02-05 | Updated: 2022-06-29
Reconstructing Training Data with Informed Adversaries
Authors: Borja Balle, Giovanni Cherubin, Jamie Hayes | Published: 2022-01-13 | Updated: 2022-04-25
Challenges and Approaches for Mitigating Byzantine Attacks in Federated Learning
Authors: Junyu Shi, Wei Wan, Shengshan Hu, Jianrong Lu, Leo Yu Zhang | Published: 2021-12-29 | Updated: 2022-10-07
Detect & Reject for Transferability of Black-box Adversarial Attacks Against Network Intrusion Detection Systems
Authors: Islam Debicha, Thibault Debatty, Jean-Michel Dricot, Wim Mees, Tayeb Kenaza | Published: 2021-12-22
Distributed Machine Learning and the Semblance of Trust
Authors: Dmitrii Usynin, Alexander Ziller, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis | Published: 2021-12-21
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey
Authors: Shangwei Guo, Xu Zhang, Fei Yang, Tianwei Zhang, Yan Gan, Tao Xiang, Yang Liu | Published: 2021-12-19
Robustifying automatic speech recognition by extracting slowly varying features
Authors: Matías Pizarro, Dorothea Kolossa, Asja Fischer | Published: 2021-12-14 | Updated: 2024-11-06
On the Security & Privacy in Federated Learning
Authors: Gorka Abad, Stjepan Picek, Víctor Julio Ramírez-Durán, Aitor Urbieta | Published: 2021-12-10 | Updated: 2022-03-16