Saved in:
| Main Authors: | Wen, Yanhua, Ai, Lu, Liu, Gang, Li, Chuang, Wei, Jianhao |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.12851 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
TinyGuard:A lightweight Byzantine Defense for Resource-Constrained Federated Learning via Statistical Update Fingerprints
by: Mahdavi, Ali, et al.
Published: (2026)
by: Mahdavi, Ali, et al.
Published: (2026)
Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
Understanding Byzantine Robustness in Federated Learning with A Black-box Server
by: Zhao, Fangyuan, et al.
Published: (2024)
by: Zhao, Fangyuan, et al.
Published: (2024)
MARS: A Malignity-Aware Backdoor Defense in Federated Learning
by: Wan, Wei, et al.
Published: (2025)
by: Wan, Wei, 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-Preserving Aggregation for Decentralized Learning with Byzantine-Robustness
by: Ghavamipour, Ali Reza, et al.
Published: (2024)
by: Ghavamipour, Ali Reza, 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)
Privacy-preserving Quantification of Non-IID Degree in Federated Learning
by: Yan, Yuping, et al.
Published: (2024)
by: Yan, Yuping, et al.
Published: (2024)
FedP3E: Privacy-Preserving Prototype Exchange for Non-IID IoT Malware Detection in Cross-Silo Federated Learning
by: Darwish, Rami, et al.
Published: (2025)
by: Darwish, Rami, et al.
Published: (2025)
CAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks on their Internal Representations
by: Li, Xiaohu, et al.
Published: (2025)
by: Li, Xiaohu, 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)
FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users
by: Rahulamathavan, Yogachandran, et al.
Published: (2023)
by: Rahulamathavan, Yogachandran, et al.
Published: (2023)
Byzantine-Robust Decentralized Federated Learning
by: Fang, Minghong, et al.
Published: (2024)
by: Fang, Minghong, et al.
Published: (2024)
SAID: Safety-Aware Intent Defense via Prefix Probing for Large Language Models
by: Chen, Yulong, et al.
Published: (2025)
by: Chen, Yulong, et al.
Published: (2025)
Federated Learning Resilient to Byzantine Attacks and Data Heterogeneity
by: Zuo, Shiyuan, et al.
Published: (2024)
by: Zuo, Shiyuan, et al.
Published: (2024)
Efficient Byzantine-Robust Privacy-Preserving Federated Learning via Dimension Compression
by: Qin, Xian, et al.
Published: (2025)
by: Qin, Xian, et al.
Published: (2025)
AdaBFL: Multi-Layer Defensive Adaptive Aggregation for Bzantine-Robust Federated Learning
by: Tang, Zehui, et al.
Published: (2026)
by: Tang, Zehui, et al.
Published: (2026)
Enhancing Security and Privacy in Federated Learning using Low-Dimensional Update Representation and Proximity-Based Defense
by: Li, Wenjie, et al.
Published: (2024)
by: Li, Wenjie, et al.
Published: (2024)
FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs
by: Han, Shanshan, et al.
Published: (2023)
by: Han, Shanshan, et al.
Published: (2023)
Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification
by: Lin, Xinjie, et al.
Published: (2025)
by: Lin, Xinjie, et al.
Published: (2025)
Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning
by: Nie, Chenfei, et al.
Published: (2024)
by: Nie, Chenfei, et al.
Published: (2024)
AMDS: Attack-Aware Multi-Stage Defense System for Network Intrusion Detection with Two-Stage Adaptive Weight Learning
by: Olukola, Oluseyi, et al.
Published: (2026)
by: Olukola, Oluseyi, et al.
Published: (2026)
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)
Coded Robust Aggregation for Distributed Learning under Byzantine Attacks
by: Li, Chengxi, et al.
Published: (2025)
by: Li, Chengxi, et al.
Published: (2025)
Hybrid Reputation Aggregation: A Robust Defense Mechanism for Adversarial Federated Learning in 5G and Edge Network Environments
by: Sheikhi, Saeid, et al.
Published: (2025)
by: Sheikhi, Saeid, et al.
Published: (2025)
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning
by: Xu, Runhua, et al.
Published: (2025)
by: Xu, Runhua, et al.
Published: (2025)
PROTEAN: Federated Intrusion Detection in Non-IID Environments through Prototype-Based Knowledge Sharing
by: Chennoufi, Sara, et al.
Published: (2025)
by: Chennoufi, Sara, et al.
Published: (2025)
Federated Learning in the Wild: A Comparative Study for Cybersecurity under Non-IID and Unbalanced Settings
by: Doriguzzi-Corin, Roberto, et al.
Published: (2025)
by: Doriguzzi-Corin, Roberto, et al.
Published: (2025)
DP-BREM: Differentially-Private and Byzantine-Robust Federated Learning with Client Momentum
by: Gu, Xiaolan, et al.
Published: (2023)
by: Gu, Xiaolan, et al.
Published: (2023)
Attacking Byzantine Robust Aggregation in High Dimensions
by: Choudhary, Sarthak, et al.
Published: (2023)
by: Choudhary, Sarthak, et al.
Published: (2023)
Byzantine-Robust Federated Learning over Ring-All-Reduce Distributed Computing
by: Fang, Minghong, et al.
Published: (2025)
by: Fang, Minghong, et al.
Published: (2025)
Defense Against Model Stealing Based on Account-Aware Distribution Discrepancy
by: Mei, Jian-Ping, et al.
Published: (2025)
by: Mei, Jian-Ping, 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)
SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
by: Zhang, Heyi, et al.
Published: (2025)
by: Zhang, Heyi, et al.
Published: (2025)
Robust Federated Learning with Confidence-Weighted Filtering and GAN-Based Completion under Noisy and Incomplete Data
by: Gokcen, Alpaslan, et al.
Published: (2025)
by: Gokcen, Alpaslan, et al.
Published: (2025)
Intelligent Adaptive Federated Byzantine Agreement for Robust Blockchain Consensus
by: Nugroho, Erdhi Widyarto, et al.
Published: (2025)
by: Nugroho, Erdhi Widyarto, et al.
Published: (2025)
WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems
by: M., Sameera K., et al.
Published: (2025)
by: M., Sameera K., et al.
Published: (2025)
Local Data Quantity-Aware Weighted Averaging for Federated Learning with Dishonest Clients
by: Wu, Leming, et al.
Published: (2025)
by: Wu, Leming, et al.
Published: (2025)
ByzSFL: Achieving Byzantine-Robust Secure Federated Learning with Zero-Knowledge Proofs
by: Fan, Yongming, et al.
Published: (2025)
by: Fan, Yongming, et al.
Published: (2025)
Structure-Aware Distributed Backdoor Attacks in Federated Learning
by: Jian, Wang, et al.
Published: (2026)
by: Jian, Wang, et al.
Published: (2026)
Similar Items
-
TinyGuard:A lightweight Byzantine Defense for Resource-Constrained Federated Learning via Statistical Update Fingerprints
by: Mahdavi, Ali, et al.
Published: (2026) -
Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings
by: Arazzi, Marco, et al.
Published: (2025) -
Understanding Byzantine Robustness in Federated Learning with A Black-box Server
by: Zhao, Fangyuan, et al.
Published: (2024) -
MARS: A Malignity-Aware Backdoor Defense in Federated Learning
by: Wan, Wei, et al.
Published: (2025) -
Enabling Trustworthy Federated Learning via Remote Attestation for Mitigating Byzantine Threats
by: Zhang, Chaoyu, et al.
Published: (2025)