Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning
Authors: Xiaoting Lyu, Yufei Han, Wei Wang, Jingkai Liu, Yongsheng Zhu, Guangquan Xu, Jiqiang Liu, Xiangliang Zhang | Published: 2024-06-10
Poisoning
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
Authors: Hengzhu Liu, Ping Xiong, Tianqing Zhu, Philip S. Yu | Published: 2024-06-10
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
Authors: Zhibo Xing, Zijian Zhang, Zi'ang Zhang, Jiamou Liu, Liehuang Zhu, Giovanni Russello | Published: 2024-06-03
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning
Authors: Zhangchen Xu, Fengqing Jiang, Luyao Niu, Jinyuan Jia, Bo Li, Radha Poovendran | Published: 2024-05-31 | Updated: 2024-06-05
PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics
Authors: Sunay Bhat, Jeffrey Jiang, Omead Pooladzandi, Alexander Branch, Gregory Pottie | Published: 2024-05-28 | Updated: 2024-06-02
Revisit, Extend, and Enhance Hessian-Free Influence Functions
Authors: Ziao Yang, Han Yue, Jian Chen, Hongfu Liu | Published: 2024-05-25 | Updated: 2024-10-20
BadGD: A unified data-centric framework to identify gradient descent vulnerabilities
Authors: Chi-Hua Wang, Guang Cheng | Published: 2024-05-24
A GAN-Based Data Poisoning Attack Against Federated Learning Systems and Its Countermeasure
Authors: Wei Sun, Bo Gao, Ke Xiong, Yuwei Wang | Published: 2024-05-19 | Updated: 2024-05-21
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy
Authors: Yichuan Shi, Olivera Kotevska, Viktor Reshniak, Abhishek Singh, Ramesh Raskar | Published: 2024-05-16
Differentially Private Federated Learning: A Systematic Review
Authors: Jie Fu, Yuan Hong, Xinpeng Ling, Leixia Wang, Xun Ran, Zhiyu Sun, Wendy Hui Wang, Zhili Chen, Yang Cao | Published: 2024-05-14 | Updated: 2024-05-20