Improving $(α, f)$-Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distance
Fuente:
arXiv
Saved in:
| Main Authors: | García-Márquez, Mario, Rodríguez-Barroso, Nuria, Luzón, M. Victoria, Herrera, Francisco |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Krum Federated Chain (KFC): Using blockchain to defend against adversarial attacks in Federated Learning
by: García-Márquez, Mario, et al.
Published: (2025)
by: García-Márquez, Mario, et al.
Published: (2025)
Resilient Federated Chain: Transforming Blockchain Consensus into an Active Defense Layer for Federated Learning
by: García-Márquez, Mario, et al.
Published: (2026)
by: García-Márquez, Mario, et al.
Published: (2026)
RAB$^2$-DEF: Dynamic and explainable defense against adversarial attacks in Federated Learning to fair poor clients
by: Rodríguez-Barroso, Nuria, et al.
Published: (2024)
by: Rodríguez-Barroso, Nuria, et al.
Published: (2024)
From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0
by: Rodríguez-Barroso, Nuria, et al.
Published: (2025)
by: Rodríguez-Barroso, Nuria, et al.
Published: (2025)
Addressing Data Quality Decompensation in Federated Learning via Dynamic Client Selection
by: Fei, Qinjun, et al.
Published: (2025)
by: Fei, Qinjun, et al.
Published: (2025)
Byzantine-Resilient Federated Learning via Distributed Optimization
by: Xia, Yufei, et al.
Published: (2025)
by: Xia, Yufei, et al.
Published: (2025)
An Interpretable Client Decision Tree Aggregation process for Federated Learning
by: Argente-Garrido, Alberto, et al.
Published: (2024)
by: Argente-Garrido, Alberto, et al.
Published: (2024)
Membership Inference Attacks fueled by Few-Short Learning to detect privacy leakage tackling data integrity
by: Jiménez-López, Daniel, et al.
Published: (2025)
by: Jiménez-López, Daniel, et al.
Published: (2025)
FLEX: FLEXible Federated Learning Framework
by: Herrera, Francisco, et al.
Published: (2024)
by: Herrera, Francisco, et al.
Published: (2024)
Federated Learning Resilient to Byzantine Attacks and Data Heterogeneity
by: Zuo, Shiyuan, et al.
Published: (2024)
by: Zuo, Shiyuan, et al.
Published: (2024)
On the Byzantine-Resilience of Distillation-Based Federated Learning
by: Roux, Christophe, et al.
Published: (2024)
by: Roux, Christophe, et al.
Published: (2024)
Communication-Efficient Byzantine-Resilient Federated Zero-Order Optimization
by: Neto, Afonso de Sá Delgado, et al.
Published: (2024)
by: Neto, Afonso de Sá Delgado, et al.
Published: (2024)
Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning
by: Ma, Hui, et al.
Published: (2025)
by: Ma, Hui, et al.
Published: (2025)
Byzantine-Robust Aggregation for Securing Decentralized Federated Learning
by: Cajaraville-Aboy, Diego, et al.
Published: (2024)
by: Cajaraville-Aboy, Diego, et al.
Published: (2024)
Byzantine-Resilient Federated Learning via QUBO-Based Client Selection on Quantum Annealers
by: Ferenczi, Andras, et al.
Published: (2026)
by: Ferenczi, Andras, et al.
Published: (2026)
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning
by: Zhao, Puning, et al.
Published: (2023)
by: Zhao, Puning, et al.
Published: (2023)
Certifiably Byzantine-Robust Federated Conformal Prediction
by: Kang, Mintong, et al.
Published: (2024)
by: Kang, Mintong, et al.
Published: (2024)
GRANITE : a Byzantine-Resilient Dynamic Gossip Learning Framework
by: Belal, Yacine, et al.
Published: (2025)
by: Belal, Yacine, et al.
Published: (2025)
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
by: Lee, Younghan, et al.
Published: (2024)
by: Lee, Younghan, et al.
Published: (2024)
FedPS: Federated data Preprocessing via aggregated Statistics
by: Xu, Xuefeng, et al.
Published: (2026)
by: Xu, Xuefeng, et al.
Published: (2026)
OptiGradTrust: Byzantine-Robust Federated Learning with Multi-Feature Gradient Analysis and Reinforcement Learning-Based Trust Weighting
by: Karami, Mohammad, et al.
Published: (2025)
by: Karami, Mohammad, et al.
Published: (2025)
BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning
by: Liu, Yi, et al.
Published: (2024)
by: Liu, Yi, et al.
Published: (2024)
Coding-Enforced Resilient and Secure Aggregation for Hierarchical Federated Learning
by: Weng, Shudi, et al.
Published: (2026)
by: Weng, Shudi, et al.
Published: (2026)
Agentic Trust Coordination for Federated Learning through Adaptive Thresholding and Autonomous Decision Making in Sustainable and Resilient Industrial Networks
by: Shepherd, Paul, et al.
Published: (2026)
by: Shepherd, Paul, et al.
Published: (2026)
Early prediction of the risk of ICU mortality with Deep Federated Learning
by: Randl, Korbinian, et al.
Published: (2022)
by: Randl, Korbinian, et al.
Published: (2022)
Trust and Resilience in Federated Learning Through Smart Contracts Enabled Decentralized Systems
by: Cassano, Lorenzo, et al.
Published: (2024)
by: Cassano, Lorenzo, et al.
Published: (2024)
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning
by: Ozfatura, Kerem, et al.
Published: (2022)
by: Ozfatura, Kerem, et al.
Published: (2022)
Personalized Federated Dictionary Learning for Modeling Heterogeneity in Multi-site fMRI Data
by: Zhang, Yipu, et al.
Published: (2025)
by: Zhang, Yipu, et al.
Published: (2025)
Improved Generalization Bounds for Communication Efficient Federated Learning
by: Gholami, Peyman, et al.
Published: (2024)
by: Gholami, Peyman, et al.
Published: (2024)
Coded Robust Aggregation for Distributed Learning under Byzantine Attacks
by: Li, Chengxi, et al.
Published: (2025)
by: Li, Chengxi, et al.
Published: (2025)
Resilient Byzantine Agreement with Predictions
by: Dallot, Julien, et al.
Published: (2026)
by: Dallot, Julien, et al.
Published: (2026)
ARMOR: Adaptive Resilience Against Model Poisoning Attacks in Continual Federated Learning for Mobile Indoor Localization
by: Gufran, Danish, et al.
Published: (2026)
by: Gufran, Danish, et al.
Published: (2026)
Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data
by: Zhou, Tailin, et al.
Published: (2023)
by: Zhou, Tailin, et al.
Published: (2023)
Improving Early Sepsis Onset Prediction Through Federated Learning
by: Düsing, Christoph, et al.
Published: (2025)
by: Düsing, Christoph, et al.
Published: (2025)
DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation
by: Herath, Charuka, et al.
Published: (2025)
by: Herath, Charuka, et al.
Published: (2025)
Federated Learning Framework via Distributed Mutual Learning
by: Gupta, Yash
Published: (2025)
by: Gupta, Yash
Published: (2025)
Enhancing Robustness of Federated Learning via Server Learning
by: Mai, Van Sy, et al.
Published: (2026)
by: Mai, Van Sy, et al.
Published: (2026)
Personalized Federated Learning via Learning Dynamic Graphs
by: Zhou, Ziran, et al.
Published: (2025)
by: Zhou, Ziran, et al.
Published: (2025)
Enabling Trustworthy Federated Learning via Remote Attestation for Mitigating Byzantine Threats
by: Zhang, Chaoyu, et al.
Published: (2025)
by: Zhang, Chaoyu, et al.
Published: (2025)
Privacy and Accuracy Implications of Model Complexity and Integration in Heterogeneous Federated Learning
by: Németh, Gergely Dániel, et al.
Published: (2023)
by: Németh, Gergely Dániel, et al.
Published: (2023)
Similar Items
-
Krum Federated Chain (KFC): Using blockchain to defend against adversarial attacks in Federated Learning
by: García-Márquez, Mario, et al.
Published: (2025) -
Resilient Federated Chain: Transforming Blockchain Consensus into an Active Defense Layer for Federated Learning
by: García-Márquez, Mario, et al.
Published: (2026) -
RAB$^2$-DEF: Dynamic and explainable defense against adversarial attacks in Federated Learning to fair poor clients
by: Rodríguez-Barroso, Nuria, et al.
Published: (2024) -
From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0
by: Rodríguez-Barroso, Nuria, et al.
Published: (2025) -
Addressing Data Quality Decompensation in Federated Learning via Dynamic Client Selection
by: Fei, Qinjun, et al.
Published: (2025)