MUBox: A Critical Evaluation Framework of Deep Machine Unlearning
Authors: Xiang Li, Bhavani Thuraisingham, Wenqi Wei | Published: 2025-05-13
Detection of Poisonous Data
Traceback of Poisoning Attacks to Retrieval-Augmented Generation
Authors: Baolei Zhang, Haoran Xin, Minghong Fang, Zhuqing Liu, Biao Yi, Tong Li, Zheli Liu | Published: 2025-04-30
Learning and Generalization with Mixture Data
Authors: Harsh Vardhan, Avishek Ghosh, Arya Mazumdar | Published: 2025-04-29
Is poisoning a real threat to LLM alignment? Maybe more so than you think
Authors: Pankayaraj Pathmanathan, Souradip Chakraborty, Xiangyu Liu, Yongyuan Liang, Furong Huang | Published: 2024-06-17 | Updated: 2025-06-09
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications
Authors: Ali Raza, Shujun Li, Kim-Phuc Tran, Ludovic Koehl, Kim Duc Tran | Published: 2022-07-18 | Updated: 2025-03-25
Deep k-NN Defense against Clean-label Data Poisoning Attacks
Authors: Neehar Peri, Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson | Published: 2019-09-29 | Updated: 2020-08-13
Is feature selection secure against training data poisoning?
Authors: Huang Xiao, Battista Biggio, Gavin Brown, Giorgio Fumera, Claudia Eckert, Fabio Roli | Published: 2018-04-21
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
Authors: Ali Shafahi, W. Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, Tom Goldstein | Published: 2018-04-03 | Updated: 2018-11-10
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
Authors: Matthew Jagielski, Alina Oprea, Battista Biggio, Chang Liu, Cristina Nita-Rotaru, Bo Li | Published: 2018-04-01 | Updated: 2021-09-28
BEBP: An Poisoning Method Against Machine Learning Based IDSs
Authors: Pan Li, Qiang Liu, Wentao Zhao, Dongxu Wang, Siqi Wang | Published: 2018-03-11