Securing Federated Sensitive Topic Classification against Poisoning Attacks

31 January 2022

Papers citing "Securing Federated Sensitive Topic Classification against Poisoning Attacks"

8 / 8 papers shown

Title
Do We Really Need to Design New Byzantine-robust Aggregation Rules? Minghong Fang Seyedsina Nabavirazavi Zhuqing Liu Wei Sun S. Iyengar Haibo Yang AAML OOD 81 6 0 29 Jan 2025
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning Zhangchen Xu Fengqing Jiang Luyao Niu Jinyuan Jia Bo Li Radha Poovendran FedML 52 1 0 31 May 2024
FedQV: Leveraging Quadratic Voting in Federated Learning Tianyue Chu Nikolaos Laoutaris FedML 24 2 0 02 Jan 2024
FLTracer: Accurate Poisoning Attack Provenance in Federated Learning Xinyu Zhang Qingyu Liu Zhongjie Ba Yuan Hong Tianhang Zheng Feng Lin Liwang Lu Kui Ren AAML 34 10 0 20 Oct 2023
Location Leakage in Federated Signal Maps Evita Bakopoulou Justin Ley Jiang Zhang Konstantinos Psounis A. Markopoulou FedML 20 5 0 07 Dec 2021
Federated Learning: Opportunities and Challenges P. Mammen FedML 48 211 0 14 Jan 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 117 611 0 27 Dec 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 188 1,032 0 29 Nov 2018