Privacy and Robustness in Federated Learning: Attacks and Defenses

Privacy and Robustness in Federated Learning: Attacks and Defenses

7 December 2020

Lichao Sun

Jun Zhao

Philip S. Yu

Papers citing "Privacy and Robustness in Federated Learning: Attacks and Defenses"

11 / 11 papers shown

Title
FedSlate:A Federated Deep Reinforcement Learning Recommender System Yongxin Deng Xihe Qiu Xiaoyu Tan Yaochu Jin FedML 44 0 0 23 Sep 2024
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions Weiming Zhuang Chen Chen Lingjuan Lyu C. L. P. Chen Yaochu Jin Lingjuan Lyu AIFin AI4CE 44 83 0 27 Jun 2023
CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks Xuanli He Qiongkai Xu Yi Zeng Lingjuan Lyu Fangzhao Wu Jiwei Li R. Jia WaLM 130 53 0 19 Sep 2022
CalFAT: Calibrated Federated Adversarial Training with Label Skewness Chen Chen Yuchen Liu Xingjun Ma Lingjuan Lyu FedML 115 23 0 30 May 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 142 314 0 15 Dec 2021
Protecting Intellectual Property of Language Generation APIs with Lexical Watermark Xuanli He Qiongkai Xu Lingjuan Lyu Fangzhao Wu Chenguang Wang WaLM 130 76 0 05 Dec 2021
Clean-Label Backdoor Attacks on Video Recognition Models Shihao Zhao Xingjun Ma Xiang Zheng James Bailey Jingjing Chen Yu-Gang Jiang AAML 139 252 0 06 Mar 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 159 392 0 04 Mar 2020
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 127 245 0 02 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 156 878 0 29 Nov 2018
Securing Distributed Gradient Descent in High Dimensional Statistical Learning Lili Su Jiaming Xu FedML 111 33 0 26 Apr 2018