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The distributed nature of training makes Federated Learning (FL) vulnerable to backdoor attacks, where malicious model updates aim to compromise the global model's performance on specific tasks.
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Dba: Distributed backdoor attacks against federated learning
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Why gradient clipping accelerates training: A theoretical justification for adaptivity
Jingzhao Zhang, Tianxing He, Suvrit Sra, and Ali Jadbabaie · 2019
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How to backdoor federated learning
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Robust aggregation for federated learning
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A comprehensive survey on poisoning attacks and countermeasures in machine learning
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Neurotoxin: Durable backdoors in federated learning
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On the vulnerability of backdoor defenses for federated learning
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Federated learning with sparsified model perturbation: Improving accuracy under client-level differential privacy
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Collaborative learning in the jungle (decentralized, byzantine, heterogeneous, asynchronous and nonconvex learning)
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Manipulating the byzantine: Optimizing model poisoning attacks and defenses for federated learning
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Signguard: Byzantine-robust federated learning through collaborative malicious gradient filtering
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Perdoor: Persistent non-uniform backdoors in federated learning using adversarial perturbations
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Byzantine machine learning made easy by resilient averaging of momentums
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Multi-metrics adaptively identifies backdoors in federated learning
Siquan Huang, Yijiang Li, Chong Chen, Leyu Shi, and Ying Gao · 2023
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Mesas: Poisoning defense for federated learning resilient against adaptive attackers
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Poisoning with cerberus: Stealthy and colluded backdoor attack against federated learning
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Grigory Malinovsky, Peter Richtárik, Samuel Horváth, and Eduard Gorbunov · 2023
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Lockdown: Backdoor defense for federated learning with isolated subspace training
Tiansheng Huang, Sihao Hu, Ka-Ho Chow, Fatih Ilhan, Selim Tekin, and Ling Liu · 2024
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Automatic adversarial adaption for stealthy poisoning attacks in federated learning
Torsten Krauß, Jan König, Alexandra Dmitrienko, and Christian Kanzow · 2024
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Iba: Towards irreversible backdoor attacks in federated learning
Thuy Dung Nguyen, Tuan A Nguyen, Anh Tran, Khoa D Doan, and Kok-Seng Wong · 2024
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A3fl: Adversarially adaptive backdoor attacks to federated learning
Hangfan Zhang, Jinyuan Jia, Jinghui Chen, Lu Lin, and Dinghao Wu · 2024
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