Model-Targeted Poisoning Attacks with Provable Convergence
Authors: Fnu Suya, Saeed Mahloujifar, Anshuman Suri, David Evans, Yuan Tian | Published: 2020-06-30 | Updated: 2021-04-21
ポイズニング
Orthogonal Deep Models As Defense Against Black-Box Attacks
Authors: Mohammad A. A. K. Jalwana, Naveed Akhtar, Mohammed Bennamoun, Ajmal Mian | Published: 2020-06-26
Deep Partition Aggregation: Provable Defense against General Poisoning Attacks
Authors: Alexander Levine, Soheil Feizi | Published: 2020-06-26 | Updated: 2021-03-18
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability
Authors: Kaizhao Liang, Jacky Y. Zhang, Boxin Wang, Zhuolin Yang, Oluwasanmi Koyejo, Bo Li | Published: 2020-06-25 | Updated: 2021-07-08
Subpopulation Data Poisoning Attacks
Authors: Matthew Jagielski, Giorgio Severi, Niklas Pousette Harger, Alina Oprea | Published: 2020-06-24 | Updated: 2021-05-12
ByGARS: Byzantine SGD with Arbitrary Number of Attackers
Authors: Jayanth Regatti, Hao Chen, Abhishek Gupta | Published: 2020-06-24 | Updated: 2020-12-07
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
Authors: Cassidy Laidlaw, Sahil Singla, Soheil Feizi | Published: 2020-06-22 | Updated: 2021-07-04
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks
Authors: Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P Dickerson, Tom Goldstein | Published: 2020-06-22 | Updated: 2021-06-17
With Great Dispersion Comes Greater Resilience: Efficient Poisoning Attacks and Defenses for Linear Regression Models
Authors: Jialin Wen, Benjamin Zi Hao Zhao, Minhui Xue, Alina Oprea, Haifeng Qian | Published: 2020-06-21 | Updated: 2021-05-19
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
Authors: Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, Qiang Yang | Published: 2020-06-20 | Updated: 2020-06-23