Backdoor Federated Learning by Poisoning Backdoor-Critical Layers
Authors: Haomin Zhuang, Mingxian Yu, Hao Wang, Yang Hua, Jian Li, Xu Yuan | Published: 2023-08-08 | Updated: 2024-04-15
Defense Method
A reading survey on adversarial machine learning: Adversarial attacks and their understanding
Authors: Shashank Kotyan | Published: 2023-08-07
Membership Inference Attacks against Language Models via Neighbourhood Comparison
Authors: Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick | Published: 2023-05-29 | Updated: 2023-08-07
COLLIDER: A Robust Training Framework for Backdoor Data
Authors: Hadi M. Dolatabadi, Sarah Erfani, Christopher Leckie | Published: 2022-10-13
PUF-Phenotype: A Robust and Noise-Resilient Approach to Aid Intra-Group-based Authentication with DRAM-PUFs Using Machine Learning
Authors: Owen Millwood, Jack Miskelly, Bohao Yang, Prosanta Gope, Elif Kavun, Chenghua Lin | Published: 2022-07-11
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy
Authors: Raphael Olivier, Bhiksha Raj | Published: 2022-07-08 | Updated: 2023-08-10
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms
Authors: Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif | Published: 2022-07-05
Defending against the Label-flipping Attack in Federated Learning
Authors: Najeeb Moharram Jebreel, Josep Domingo-Ferrer, David Sánchez, Alberto Blanco-Justicia | Published: 2022-07-05
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems
Authors: Shail Dave, Alberto Marchisio, Muhammad Abdullah Hanif, Amira Guesmi, Aviral Shrivastava, Ihsen Alouani, Muhammad Shafique | Published: 2022-04-18
Machine Learning Security against Data Poisoning: Are We There Yet?
Authors: Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo | Published: 2022-04-12 | Updated: 2024-03-08