Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive Sparsified Model Aggregation
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Xu, Jiahao, Zhang, Zikai, Hu, Rui |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Identify Backdoored Model in Federated Learning via Individual Unlearning
par: Xu, Jiahao, et autres
Publié: (2024)
par: Xu, Jiahao, et autres
Publié: (2024)
Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection
par: Xu, Jiahao, et autres
Publié: (2025)
par: Xu, Jiahao, et autres
Publié: (2025)
Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning
par: Xu, Zhangchen, et autres
Publié: (2024)
par: Xu, Zhangchen, et autres
Publié: (2024)
Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises
par: Xia, Yue, et autres
Publié: (2024)
par: Xia, Yue, et autres
Publié: (2024)
Byzantine-Resilient Zero-Order Optimization for Communication-Efficient Heterogeneous Federated Learning
par: Egger, Maximilian, et autres
Publié: (2025)
par: Egger, Maximilian, et autres
Publié: (2025)
Byzantine-Robust Decentralized Federated Learning
par: Fang, Minghong, et autres
Publié: (2024)
par: Fang, Minghong, et autres
Publié: (2024)
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
par: Xing, Zhibo, et autres
Publié: (2024)
par: Xing, Zhibo, et autres
Publié: (2024)
Practical Framework for Privacy-Preserving and Byzantine-robust Federated Learning
par: Zhang, Baolei, et autres
Publié: (2025)
par: Zhang, Baolei, et autres
Publié: (2025)
Enhancing Federated Learning with Adaptive Differential Privacy and Priority-Based Aggregation
par: Talaei, Mahtab, et autres
Publié: (2024)
par: Talaei, Mahtab, et autres
Publié: (2024)
DisAgg: Distributed Aggregators for Efficient Secure Aggregation in Federated Learning
par: Mehmood, Haaris, et autres
Publié: (2026)
par: Mehmood, Haaris, et autres
Publié: (2026)
Aggressive or Imperceptible, or Both: Network Pruning Assisted Hybrid Byzantines in Federated Learning
par: Ozfatura, Emre, et autres
Publié: (2024)
par: Ozfatura, Emre, et autres
Publié: (2024)
Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective
par: Zhang, Zhongjian, et autres
Publié: (2025)
par: Zhang, Zhongjian, et autres
Publié: (2025)
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
par: Fang, Minghong, et autres
Publié: (2025)
par: Fang, Minghong, et autres
Publié: (2025)
The Robustness of Spiking Neural Networks in Federated Learning with Compression Against Non-omniscient Byzantine Attacks
par: Nguyen, Manh V., et autres
Publié: (2025)
par: Nguyen, Manh V., et autres
Publié: (2025)
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
par: Lee, Younghan, et autres
Publié: (2024)
par: Lee, Younghan, et autres
Publié: (2024)
FedBaF: Federated Learning Aggregation Biased by a Foundation Model
par: Park, Jong-Ik, et autres
Publié: (2024)
par: Park, Jong-Ik, et autres
Publié: (2024)
Federated Graph Learning with Adaptive Importance-based Sampling
par: Li, Anran, et autres
Publié: (2024)
par: Li, Anran, et autres
Publié: (2024)
Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex Hulls
par: Prakash, Saurav, et autres
Publié: (2023)
par: Prakash, Saurav, et autres
Publié: (2023)
Private Aggregation in Hierarchical Wireless Federated Learning with Partial and Full Collusion
par: Egger, Maximilian, et autres
Publié: (2023)
par: Egger, Maximilian, et autres
Publié: (2023)
On the Tradeoff between Privacy Preservation and Byzantine-Robustness in Decentralized Learning
par: Ye, Haoxiang, et autres
Publié: (2023)
par: Ye, Haoxiang, et autres
Publié: (2023)
DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation
par: Herath, Charuka, et autres
Publié: (2025)
par: Herath, Charuka, et autres
Publié: (2025)
An Adaptive Multi-Layered Honeynet Architecture for Threat Behavior Analysis via Deep Learning
par: Möller, Lukas Johannes
Publié: (2025)
par: Möller, Lukas Johannes
Publié: (2025)
FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning
par: Zhang, Jianqing, et autres
Publié: (2024)
par: Zhang, Jianqing, et autres
Publié: (2024)
LIFT: Byzantine Resilient Hub-Sampling
par: Legheraba, Mohamed Amine, et autres
Publié: (2026)
par: Legheraba, Mohamed Amine, et autres
Publié: (2026)
ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated Learning Based on Coded Computing and Vector Commitment
par: Jahani-Nezhad, Tayyebeh, et autres
Publié: (2023)
par: Jahani-Nezhad, Tayyebeh, et autres
Publié: (2023)
A Whole-Process Certifiably Robust Aggregation Method Against Backdoor Attacks in Federated Learning
par: Zhou, Anqi, et autres
Publié: (2024)
par: Zhou, Anqi, et autres
Publié: (2024)
Efficient Language Model Architectures for Differentially Private Federated Learning
par: Ro, Jae Hun, et autres
Publié: (2024)
par: Ro, Jae Hun, et autres
Publié: (2024)
On the Hardness of Decentralized Multi-Agent Policy Evaluation under Byzantine Attacks
par: Hairi, et autres
Publié: (2024)
par: Hairi, et autres
Publié: (2024)
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers
par: Liu, Wenyu, et autres
Publié: (2023)
par: Liu, Wenyu, et autres
Publié: (2023)
Chu-ko-nu: A Reliable, Efficient, and Anonymously Authentication-Enabled Realization for Multi-Round Secure Aggregation in Federated Learning
par: Cui, Kaiping, et autres
Publié: (2024)
par: Cui, Kaiping, et autres
Publié: (2024)
Deep Transfer Hashing for Adaptive Learning on Federated Streaming Data
par: Röder, Manuel, et autres
Publié: (2024)
par: Röder, Manuel, et autres
Publié: (2024)
Differentially Private Federated Learning With Time-Adaptive Privacy Spending
par: Kiani, Shahrzad, et autres
Publié: (2025)
par: Kiani, Shahrzad, et autres
Publié: (2025)
Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning
par: Zhang, Hangtao, et autres
Publié: (2023)
par: Zhang, Hangtao, et autres
Publié: (2023)
Adaptive Differential Privacy in Federated Learning: A Priority-Based Approach
par: Talaei, Mahtab, et autres
Publié: (2024)
par: Talaei, Mahtab, et autres
Publié: (2024)
Personalized Federated Learning via Stacking
par: Cantu-Cervini, Emilio
Publié: (2024)
par: Cantu-Cervini, Emilio
Publié: (2024)
Towards Trustworthy Federated Learning
par: Basharat, Alina, et autres
Publié: (2025)
par: Basharat, Alina, et autres
Publié: (2025)
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning
par: Ozfatura, Kerem, et autres
Publié: (2022)
par: Ozfatura, Kerem, et autres
Publié: (2022)
Upcycling Noise for Federated Unlearning
par: Chen, Jianan, et autres
Publié: (2024)
par: Chen, Jianan, et autres
Publié: (2024)
Identifying the Truth of Global Model: A Generic Solution to Defend Against Byzantine and Backdoor Attacks in Federated Learning (full version)
par: Ebron, Sheldon C., et autres
Publié: (2023)
par: Ebron, Sheldon C., et autres
Publié: (2023)
DROP: Poison Dilution via Knowledge Distillation for Federated Learning
par: Syros, Georgios, et autres
Publié: (2025)
par: Syros, Georgios, et autres
Publié: (2025)
Documents similaires
-
Identify Backdoored Model in Federated Learning via Individual Unlearning
par: Xu, Jiahao, et autres
Publié: (2024) -
Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection
par: Xu, Jiahao, et autres
Publié: (2025) -
Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning
par: Xu, Zhangchen, et autres
Publié: (2024) -
Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises
par: Xia, Yue, et autres
Publié: (2024) -
Byzantine-Resilient Zero-Order Optimization for Communication-Efficient Heterogeneous Federated Learning
par: Egger, Maximilian, et autres
Publié: (2025)