Provably effective detection of effective data poisoning attacks
Authors: Jonathan Gallagher, Yasaman Esfandiari, Callen MacPhee, Michael Warren | Published: 2025-01-21
Poisoning
VerifBFL: Leveraging zk-SNARKs for A Verifiable Blockchained Federated Learning
Authors: Ahmed Ayoub Bellachia, Mouhamed Amine Bouchiha, Yacine Ghamri-Doudane, Mourad Rabah | Published: 2025-01-08
Mingling with the Good to Backdoor Federated Learning
Authors: Nuno Neves | Published: 2025-01-03
A Backdoor Attack Scheme with Invisible Triggers Based on Model Architecture Modification
Authors: Yuan Ma, Xu Ma, Jiankang Wei, Jinmeng Tang, Xiaoyu Zhang, Yilun Lyu, Kehao Chen, Jingtong Huang | Published: 2024-12-22 | Updated: 2025-01-06
Adversarially robust generalization theory via Jacobian regularization for deep neural networks
Authors: Dongya Wu, Xin Li | Published: 2024-12-17
GLL: A Differentiable Graph Learning Layer for Neural Networks
Authors: Jason Brown, Bohan Chen, Harris Hardiman-Mostow, Jeff Calder, Andrea L. Bertozzi | Published: 2024-12-11
Optimal Defenses Against Gradient Reconstruction Attacks
Authors: Yuxiao Chen, Gamze Gürsoy, Qi Lei | Published: 2024-11-06
FEDLAD: Federated Evaluation of Deep Leakage Attacks and Defenses
Authors: Isaac Baglin, Xiatian Zhu, Simon Hadfield | Published: 2024-11-05 | Updated: 2025-01-05
Federated Learning in Practice: Reflections and Projections
Authors: Katharine Daly, Hubert Eichner, Peter Kairouz, H. Brendan McMahan, Daniel Ramage, Zheng Xu | Published: 2024-10-11
PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Authors: Tingchen Fu, Mrinank Sharma, Philip Torr, Shay B. Cohen, David Krueger, Fazl Barez | Published: 2024-10-11