Papers citing 'Gradient Obfuscation Gives a False Sense of Security in Federated Learning'

Title
Privacy in Federated Learning with Spiking Neural Networks Dogukan Aksu Jesus Martinez del Rincon Ihsen Alouani AAML FedML 459 0 0 26 Nov 2025
GUIDE: Enhancing Gradient Inversion Attacks in Federated Learning with Denoising Models Vincenzo Carletti Pasquale Foggia Carlo Mazzocca Giuseppe Parrella Mario Vento AAML FedML 134 0 0 20 Oct 2025
SVDefense: Effective Defense against Gradient Inversion Attacks via Singular Value Decomposition Chenxiang Luo David K.Y. Yau Qun Song AAML 129 0 0 01 Oct 2025
Towards Privacy-Preserving and Heterogeneity-aware Split Federated Learning via Probabilistic Masking Xingchen Wang Feijie Wu Chenglin Miao Tianchun Li Haoyu Hu Qiming Cao Jing Gao Lu Su 104 0 0 18 Sep 2025
From Research to Reality: Feasibility of Gradient Inversion Attacks in Federated Learning Viktor Valadi Mattias Åkesson Johan Östman Salman Toor Andreas Hellander AAML FedML 83 0 0 27 Aug 2025
On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions Daniel Gutiérrez Yelizaveta Falkouskaya Jose L. Hernandez-Ramos Aris Anagnostopoulos I. Chatzigiannakis A. Vitaletti FedML 104 2 0 19 Aug 2025
Securing Genomic Data Against Inference Attacks in Federated Learning Environments Chetan Pathade Shubham Patil 160 2 0 12 May 2025
NET-SA: An Efficient Secure Aggregation Architecture Based on In-Network Computing Qingqing Ren Wen Wang Shuyong Zhu Zhiyuan Wu Yujun Zhang 243 0 0 02 Jan 2025
Federated Learning Nodes Can Reconstruct Peers' Image Data Ethan Wilson Kai Yue Chau-Wai Wong H. Dai FedML 244 1 0 07 Oct 2024
Edge Detectors Can Make Deep Convolutional Neural Networks More Robust Jin Ding Jie-Chao Zhao Yong-zhi Sun Ping Tan Jia-Wei Wang Ji-en Ma You-tong Fang AAML 146 3 0 26 Feb 2024
TernaryVote: Differentially Private, Communication Efficient, and Byzantine Resilient Distributed Optimization on Heterogeneous Data Richeng Jin Yujie Gu Kai Yue Xiaofan He Zhaoyang Zhang Huaiyu Dai FedML 254 1 0 16 Feb 2024
A Comprehensive Survey of Attack Techniques, Implementation, and Mitigation Strategies in Large Language Models Aysan Esmradi Daniel Wankit Yip C. Chan AAML 211 23 0 18 Dec 2023
Improving the Robustness of Transformer-based Large Language Models with Dynamic AttentionNetwork and Distributed System Security Symposium (NDSS), 2023 Lujia Shen Yuwen Pu R. Beyah Changjiang Li Xuhong Zhang Chunpeng Ge Ting Wang AAML 131 10 0 29 Nov 2023
A Privacy Preserving System for Movie Recommendations Using Federated Learning David Neumann Andreas Lutz Karsten Müller Wojciech Samek 229 16 0 07 Mar 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and PrivacyThe Web Conference (WWW), 2023 Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 316 61 0 21 Feb 2023
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning Mingyuan Fan Cen Chen Chengyu Wang Ximeng Liu Wenmeng Zhou AAML FedML 327 0 0 05 Dec 2022