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2011.02167
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BaFFLe: Backdoor detection via Feedback-based Federated Learning
4 November 2020
Sébastien Andreina
G. Marson
Helen Möllering
Ghassan O. Karame
FedML
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Papers citing
"BaFFLe: Backdoor detection via Feedback-based Federated Learning"
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118
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204
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174
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370
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317
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309
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262
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265
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252
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297
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197
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Adversarial Client Detection via Non-parametric Subspace Monitoring in the Internet of Federated Things
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197
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Fed-LSAE: Thwarting Poisoning Attacks against Federated Cyber Threat Detection System via Autoencoder-based Latent Space Inspection
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Vuong Minh Tien
N. H. Quyen
Do Thi Thu Hien
Phan The Duy
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235
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SPFL: A Self-purified Federated Learning Method Against Poisoning Attacks
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Zizhen Liu
Weiyang He
Chip-Hong Chang
Jing Ye
Huawei Li
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308
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Iraklis Varlamis
Hamza Kheddar
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FedML
254
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24 Aug 2023
FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks
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Zeyu Song
Md Rafi Ur Rashid
Shagufta Mehnaz
242
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193
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Heterogeneous Federated Learning: State-of-the-art and Research Challenges
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Differential Analysis of Triggers and Benign Features for Black-Box DNN Backdoor Detection
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Prashanth Krishnamurthy
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262
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395
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Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations
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313
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329
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241
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Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning
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240
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Multi-metrics adaptively identifies backdoors in Federated learning
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352
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12 Mar 2023
Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions
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Hieu H. Pham
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Thiemo Voigt
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274
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FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning
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Ahmad-Reza Sadeghi Technical University Darmstadt
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Privacy-Preserving Aggregation in Federated Learning: A Survey
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363
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Servio Paguada
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A. Urbieta
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246
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305
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