Certified Robust Neural Networks: Generalization and Corruption Resistance
Authors: Amine Bennouna, Ryan Lucas, Bart Van Parys | Published: 2023-03-03 | Updated: 2023-05-18
ポイズニング攻撃
Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspective
Authors: Baoyuan Wu, Zihao Zhu, Li Liu, Qingshan Liu, Zhaofeng He, Siwei Lyu | Published: 2023-02-19 | Updated: 2024-01-04
Mithridates: Auditing and Boosting Backdoor Resistance of Machine Learning Pipelines
Authors: Eugene Bagdasaryan, Vitaly Shmatikov | Published: 2023-02-09 | Updated: 2023-12-19
Temporal Robustness against Data Poisoning
Authors: Wenxiao Wang, Soheil Feizi | Published: 2023-02-07 | Updated: 2023-12-06
SoK: A Systematic Evaluation of Backdoor Trigger Characteristics in Image Classification
Authors: Gorka Abad, Jing Xu, Stefanos Koffas, Behrad Tajalli, Stjepan Picek, Mauro Conti | Published: 2023-02-03 | Updated: 2023-04-21
Suppressing Poisoning Attacks on Federated Learning for Medical Imaging
Authors: Naif Alkhunaizi, Dmitry Kamzolov, Martin Takáč, Karthik Nandakumar | Published: 2022-07-15
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics
Authors: Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh | Published: 2021-04-22
Defending Against Adversarial Denial-of-Service Data Poisoning Attacks
Authors: Nicolas M. Müller, Simon Roschmann, Konstantin Böttinger | Published: 2021-04-14 | Updated: 2021-11-30
Fall of Giants: How popular text-based MLaaS fall against a simple evasion attack
Authors: Luca Pajola, Mauro Conti | Published: 2021-04-13
SGBA: A Stealthy Scapegoat Backdoor Attack against Deep Neural Networks
Authors: Ying He, Zhili Shen, Chang Xia, Jingyu Hua, Wei Tong, Sheng Zhong | Published: 2021-04-02 | Updated: 2022-05-16