Practical Framework for Privacy-Preserving and Byzantine-robust Federated Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Baolei, Fang, Minghong, Liu, Zhuqing, Yi, Biao, Zhou, Peizhao, Wang, Yuan, Li, Tong, Liu, Zheli |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
by: Fang, Minghong, et al.
Published: (2025)
by: Fang, Minghong, et al.
Published: (2025)
Toward Malicious Clients Detection in Federated Learning
by: Dou, Zhihao, et al.
Published: (2025)
by: Dou, Zhihao, et al.
Published: (2025)
Byzantine-Robust Decentralized Federated Learning
by: Fang, Minghong, et al.
Published: (2024)
by: Fang, Minghong, et al.
Published: (2024)
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
by: Xing, Zhibo, et al.
Published: (2024)
by: Xing, Zhibo, et al.
Published: (2024)
DP2Guard: A Lightweight and Byzantine-Robust Privacy-Preserving Federated Learning Scheme for Industrial IoT
by: Han, Baofu, et al.
Published: (2025)
by: Han, Baofu, et al.
Published: (2025)
Enhancing Privacy in Decentralized Min-Max Optimization: A Differentially Private Approach
by: Quan, Yueyang, et al.
Published: (2025)
by: Quan, Yueyang, et al.
Published: (2025)
SecureAFL: Secure Asynchronous Federated Learning
by: Gao, Anjun, et al.
Published: (2026)
by: Gao, Anjun, et al.
Published: (2026)
Poisoning Attacks and Defenses to Federated Unlearning
by: Wang, Wenbin, et al.
Published: (2025)
by: Wang, Wenbin, et al.
Published: (2025)
Lancelot: Towards Efficient and Privacy-Preserving Byzantine-Robust Federated Learning within Fully Homomorphic Encryption
by: Jiang, Siyang, et al.
Published: (2024)
by: Jiang, Siyang, et al.
Published: (2024)
Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning
by: Xu, Zhangchen, et al.
Published: (2024)
by: Xu, Zhangchen, et al.
Published: (2024)
On the Hardness of Decentralized Multi-Agent Policy Evaluation under Byzantine Attacks
by: Hairi, et al.
Published: (2024)
by: Hairi, et al.
Published: (2024)
Quantum-Inspired Privacy-Preserving Federated Learning Framework for Secure Dementia Classification
by: Tanbhir, Gazi, et al.
Published: (2025)
by: Tanbhir, Gazi, et al.
Published: (2025)
On the Tradeoff between Privacy Preservation and Byzantine-Robustness in Decentralized Learning
by: Ye, Haoxiang, et al.
Published: (2023)
by: Ye, Haoxiang, et al.
Published: (2023)
EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated Learning
by: Li, Zhiqiang, et al.
Published: (2025)
by: Li, Zhiqiang, et al.
Published: (2025)
Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare System
by: Madduri, Ravi, et al.
Published: (2024)
by: Madduri, Ravi, et al.
Published: (2024)
Provably Robust Federated Reinforcement Learning
by: Fang, Minghong, et al.
Published: (2025)
by: Fang, Minghong, et al.
Published: (2025)
Find a Scapegoat: Poisoning Membership Inference Attack and Defense to Federated Learning
by: Mo, Wenjin, et al.
Published: (2025)
by: Mo, Wenjin, et al.
Published: (2025)
Privacy-Preserving Data Processing in Cloud : From Homomorphic Encryption to Federated Analytics
by: Sarraf, Gaurav, et al.
Published: (2026)
by: Sarraf, Gaurav, et al.
Published: (2026)
FedGuard: A Diverse-Byzantine-Robust Mechanism for Federated Learning with Major Malicious Clients
by: Jiang, Haocheng, et al.
Published: (2025)
by: Jiang, Haocheng, et al.
Published: (2025)
Secure and Privacy-Preserving Vertical Federated Learning
by: Jin, Shan, et al.
Published: (2026)
by: Jin, Shan, et al.
Published: (2026)
IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning
by: Riya, Farhin Farhad, et al.
Published: (2026)
by: Riya, Farhin Farhad, et al.
Published: (2026)
PPVF: An Efficient Privacy-Preserving Online Video Fetching Framework with Correlated Differential Privacy
by: Zhang, Xianzhi, et al.
Published: (2024)
by: Zhang, Xianzhi, et al.
Published: (2024)
SecureSplit: Mitigating Backdoor Attacks in Split Learning
by: Dou, Zhihao, et al.
Published: (2026)
by: Dou, Zhihao, et al.
Published: (2026)
Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks
by: Xu, Yichang, et al.
Published: (2024)
by: Xu, Yichang, et al.
Published: (2024)
HHEML: Hybrid Homomorphic Encryption for Privacy-Preserving Machine Learning on Edge
by: Chan, Yu Hin, et al.
Published: (2025)
by: Chan, Yu Hin, et al.
Published: (2025)
Lightweight Federated Learning with Differential Privacy and Straggler Resilience
by: Hong, Shu, et al.
Published: (2024)
by: Hong, Shu, et al.
Published: (2024)
LIFT: Byzantine Resilient Hub-Sampling
by: Legheraba, Mohamed Amine, et al.
Published: (2026)
by: Legheraba, Mohamed Amine, et al.
Published: (2026)
Privacy Preserving Machine Learning Model Personalization through Federated Personalized Learning
by: Hosain, Md. Tanzib, et al.
Published: (2025)
by: Hosain, Md. Tanzib, et al.
Published: (2025)
Head Count: Privacy-Preserving Face-Based Crowd Monitoring
by: Marzani, Fatemeh, et al.
Published: (2026)
by: Marzani, Fatemeh, et al.
Published: (2026)
DeZent: Decentralized z-Anonymity with Privacy-Preserving Coordination
by: Brunn, Carolin, et al.
Published: (2026)
by: Brunn, Carolin, et al.
Published: (2026)
Fantastyc: Blockchain-based Federated Learning Made Secure and Practical
by: Boitier, William, et al.
Published: (2024)
by: Boitier, William, et al.
Published: (2024)
Byzantine-Robust Federated Learning Using Generative Adversarial Networks
by: Zafar, Usama, et al.
Published: (2025)
by: Zafar, Usama, et al.
Published: (2025)
Byzantine Attacks Exploiting Penalties in Ethereum PoS
by: Pavloff, Ulysse, et al.
Published: (2024)
by: Pavloff, Ulysse, et al.
Published: (2024)
Juggernaut: Efficient Crypto-Agnostic Byzantine Agreement
by: Collins, Daniel, et al.
Published: (2024)
by: Collins, Daniel, et al.
Published: (2024)
Detect \& Score: Privacy-Preserving Misbehaviour Detection and Contribution Evaluation in Federated Learning
by: Xhemrishi, Marvin, et al.
Published: (2025)
by: Xhemrishi, Marvin, et al.
Published: (2025)
A Lightweight Federated Learning Approach for Privacy-Preserving Botnet Detection in IoT
by: Mahmoud, Taha M., et al.
Published: (2025)
by: Mahmoud, Taha M., et al.
Published: (2025)
Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises
by: Xia, Yue, et al.
Published: (2024)
by: Xia, Yue, et al.
Published: (2024)
Chop Chop: Byzantine Atomic Broadcast to the Network Limit
by: Camaioni, Martina, et al.
Published: (2023)
by: Camaioni, Martina, et al.
Published: (2023)
PPFPL: Cross-silo Privacy-preserving Federated Prototype Learning Against Data Poisoning Attacks
by: Zhang, Hongliang, et al.
Published: (2025)
by: Zhang, Hongliang, et al.
Published: (2025)
HFIPay: Privacy-Preserving, Cross-Chain Cryptocurrency Payments to Human-Friendly Identifiers
by: Wang, Jian Sheng
Published: (2026)
by: Wang, Jian Sheng
Published: (2026)
Similar Items
-
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
by: Fang, Minghong, et al.
Published: (2025) -
Toward Malicious Clients Detection in Federated Learning
by: Dou, Zhihao, et al.
Published: (2025) -
Byzantine-Robust Decentralized Federated Learning
by: Fang, Minghong, et al.
Published: (2024) -
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
by: Xing, Zhibo, et al.
Published: (2024) -
DP2Guard: A Lightweight and Byzantine-Robust Privacy-Preserving Federated Learning Scheme for Industrial IoT
by: Han, Baofu, et al.
Published: (2025)