Detect & Reject for Transferability of Black-box Adversarial Attacks Against Network Intrusion Detection Systems
Authors: Islam Debicha, Thibault Debatty, Jean-Michel Dricot, Wim Mees, Tayeb Kenaza | Published: 2021-12-22
Poisoning
Distributed Machine Learning and the Semblance of Trust
Authors: Dmitrii Usynin, Alexander Ziller, Daniel Rueckert, Jonathan Passerat-Palmbach, Georgios Kaissis | Published: 2021-12-21
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey
Authors: Shangwei Guo, Xu Zhang, Fei Yang, Tianwei Zhang, Yan Gan, Tao Xiang, Yang Liu | Published: 2021-12-19
Robustifying automatic speech recognition by extracting slowly varying features
Authors: Matías Pizarro, Dorothea Kolossa, Asja Fischer | Published: 2021-12-14 | Updated: 2024-11-06
On the Security & Privacy in Federated Learning
Authors: Gorka Abad, Stjepan Picek, Víctor Julio Ramírez-Durán, Aitor Urbieta | Published: 2021-12-10 | Updated: 2022-03-16
Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review
Authors: Huda Ali Alatwi, Charles Morisset | Published: 2021-12-06
When the Curious Abandon Honesty: Federated Learning Is Not Private
Authors: Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot | Published: 2021-12-06 | Updated: 2023-04-12
Improving Differentially Private SGD via Randomly Sparsified Gradients
Authors: Junyi Zhu, Matthew B. Blaschko | Published: 2021-12-01 | Updated: 2023-06-28
Evaluating Adversarial Attacks on ImageNet: A Reality Check on Misclassification Classes
Authors: Utku Ozbulak, Maura Pintor, Arnout Van Messem, Wesley De Neve | Published: 2021-11-22
Fooling Adversarial Training with Inducing Noise
Authors: Zhirui Wang, Yifei Wang, Yisen Wang | Published: 2021-11-19