Defense Against Gradient Leakage Attacks via Learning to Obscure Data
Authors: Yuxuan Wan, Han Xu, Xiaorui Liu, Jie Ren, Wenqi Fan, Jiliang Tang | Published: 2022-06-01
Poisoning
Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data
Authors: Huancheng Chen, Haris Vikalo | Published: 2022-06-01 | Updated: 2023-04-20
Differential Privacy: What is all the noise about?
Authors: Roxana Danger | Published: 2022-05-19
Representation learning with function call graph transformations for malware open set recognition
Authors: Jingyun Jia, Philip K. Chan | Published: 2022-05-13 | Updated: 2022-07-12
Performance Weighting for Robust Federated Learning Against Corrupted Sources
Authors: Dimitris Stripelis, Marcin Abram, Jose Luis Ambite | Published: 2022-05-02
Reducing the Cost of Training Security Classifier (via Optimized Semi-Supervised Learning)
Authors: Rui Shu, Tianpei Xia, Huy Tu, Laurie Williams, Tim Menzies | Published: 2022-05-02
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
Breaking the De-Pois Poisoning Defense
Authors: Alaa Anani, Mohamed Ghanem, Lotfy Abdel Khaliq | Published: 2022-04-03
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets
Authors: Florian Tramèr, Reza Shokri, Ayrton San Joaquin, Hoang Le, Matthew Jagielski, Sanghyun Hong, Nicholas Carlini | Published: 2022-03-31 | Updated: 2022-10-06
Privacy-Preserving Aggregation in Federated Learning: A Survey
Authors: Ziyao Liu, Jiale Guo, Wenzhuo Yang, Jiani Fan, Kwok-Yan Lam, Jun Zhao | Published: 2022-03-31 | Updated: 2022-07-13