Secure Federated Learning against Model Poisoning Attacks via Client
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Secure Federated Learning against Model Poisoning Attacks via Client Filtering

31 March 2023

Salman Avestimehr

Papers citing "Secure Federated Learning against Model Poisoning Attacks via Client Filtering"

9 / 9 papers shown

Title
Secure Cluster-Based Hierarchical Federated Learning in Vehicular Networks M. S. HaghighiFard Sinem Coleri AAML 33 0 0 02 May 2025
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning Runhua Xu Shiqi Gao Chao Li J. Joshi Jianxin Li 43 2 0 08 Feb 2025
PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning Sizai Hou Songze Li Tayyebeh Jahani-Nezhad Giuseppe Caire FedML 34 1 0 12 Jul 2024
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning Zhibo Xing Zijian Zhang Ziáng Zhang Jiamou Liu Liehuang Zhu Giovanni Russello FedML 55 2 0 03 Jun 2024
Secure Hierarchical Federated Learning in Vehicular Networks Using Dynamic Client Selection and Anomaly Detection M. S. HaghighiFard Sinem Coleri AAML 42 0 0 25 May 2024
RFLPA: A Robust Federated Learning Framework against Poisoning Attacks with Secure Aggregation Peihua Mai Ran Yan Yan Pang FedML 43 5 0 24 May 2024
Ensembler: Combating model inversion attacks using model ensemble during collaborative inference Dancheng Liu Jinjun Xiong MIACV FedML AAML 40 0 0 19 Jan 2024
FedMultimodal: A Benchmark For Multimodal Federated Learning Tiantian Feng Digbalay Bose Tuo Zhang Rajat Hebbar Anil Ramakrishna Rahul Gupta Mi Zhang Salman Avestimehr Shrikanth Narayanan 32 48 0 15 Jun 2023
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 117 611 0 27 Dec 2020