Image de couverture de livre

FLTG: Byzantine-Robust Federated Learning via Angle-Based Defense and Non-IID-Aware Weighting

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wen, Yanhua, Ai, Lu, Liu, Gang, Li, Chuang, Wei, Jianhao
Format:	Preprint
Publié:	2025
Sujets:	Cryptography and Security Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

TinyGuard:A lightweight Byzantine Defense for Resource-Constrained Federated Learning via Statistical Update Fingerprints
par: Mahdavi, Ali, et autres
Publié: (2026)

Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings
par: Arazzi, Marco, et autres
Publié: (2025)

Understanding Byzantine Robustness in Federated Learning with A Black-box Server
par: Zhao, Fangyuan, et autres
Publié: (2024)

MARS: A Malignity-Aware Backdoor Defense in Federated Learning
par: Wan, Wei, et autres
Publié: (2025)

Enabling Trustworthy Federated Learning via Remote Attestation for Mitigating Byzantine Threats
par: Zhang, Chaoyu, et autres
Publié: (2025)

Privacy-Preserving Aggregation for Decentralized Learning with Byzantine-Robustness
par: Ghavamipour, Ali Reza, et autres
Publié: (2024)

Privacy-preserving Quantification of Non-IID Degree in Federated Learning
par: Yan, Yuping, et autres
Publié: (2024)

FedP3E: Privacy-Preserving Prototype Exchange for Non-IID IoT Malware Detection in Cross-Silo Federated Learning
par: Darwish, Rami, et autres
Publié: (2025)

FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users
par: Rahulamathavan, Yogachandran, et autres
Publié: (2023)

Efficient Byzantine-Robust Privacy-Preserving Federated Learning via Dimension Compression
par: Qin, Xian, et autres
Publié: (2025)

CAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks on their Internal Representations
par: Li, Xiaohu, et autres
Publié: (2025)

Byzantine-Robust Federated Learning Using Generative Adversarial Networks
par: Zafar, Usama, et autres
Publié: (2025)

SAID: Safety-Aware Intent Defense via Prefix Probing for Large Language Models
par: Chen, Yulong, et autres
Publié: (2025)

Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning
par: Nie, Chenfei, et autres
Publié: (2024)

Enhancing Security and Privacy in Federated Learning using Low-Dimensional Update Representation and Proximity-Based Defense
par: Li, Wenjie, et autres
Publié: (2024)

FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs
par: Han, Shanshan, et autres
Publié: (2023)

Federated Learning Resilient to Byzantine Attacks and Data Heterogeneity
par: Zuo, Shiyuan, et autres
Publié: (2024)

FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
par: Lee, Younghan, et autres
Publié: (2024)

AMDS: Attack-Aware Multi-Stage Defense System for Network Intrusion Detection with Two-Stage Adaptive Weight Learning
par: Olukola, Oluseyi, et autres
Publié: (2026)

AdaBFL: Multi-Layer Defensive Adaptive Aggregation for Bzantine-Robust Federated Learning
par: Tang, Zehui, et autres
Publié: (2026)

Byzantine-Robust Decentralized Federated Learning
par: Fang, Minghong, et autres
Publié: (2024)

Hybrid Reputation Aggregation: A Robust Defense Mechanism for Adversarial Federated Learning in 5G and Edge Network Environments
par: Sheikhi, Saeid, et autres
Publié: (2025)

BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning
par: Liu, Yi, et autres
Publié: (2024)

PROTEAN: Federated Intrusion Detection in Non-IID Environments through Prototype-Based Knowledge Sharing
par: Chennoufi, Sara, et autres
Publié: (2025)

Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification
par: Lin, Xinjie, et autres
Publié: (2025)

DP-BREM: Differentially-Private and Byzantine-Robust Federated Learning with Client Momentum
par: Gu, Xiaolan, et autres
Publié: (2023)

Federated Learning in the Wild: A Comparative Study for Cybersecurity under Non-IID and Unbalanced Settings
par: Doriguzzi-Corin, Roberto, et autres
Publié: (2025)

Coded Robust Aggregation for Distributed Learning under Byzantine Attacks
par: Li, Chengxi, et autres
Publié: (2025)

Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning
par: Xu, Runhua, et autres
Publié: (2025)

Defense Against Model Stealing Based on Account-Aware Distribution Discrepancy
par: Mei, Jian-Ping, et autres
Publié: (2025)

Intelligent Adaptive Federated Byzantine Agreement for Robust Blockchain Consensus
par: Nugroho, Erdhi Widyarto, et autres
Publié: (2025)

Byzantine-Robust Federated Learning over Ring-All-Reduce Distributed Computing
par: Fang, Minghong, et autres
Publié: (2025)

ByzSFL: Achieving Byzantine-Robust Secure Federated Learning with Zero-Knowledge Proofs
par: Fan, Yongming, et autres
Publié: (2025)

WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems
par: M., Sameera K., et autres
Publié: (2025)

Attacking Byzantine Robust Aggregation in High Dimensions
par: Choudhary, Sarthak, et autres
Publié: (2023)

Robust Federated Learning with Confidence-Weighted Filtering and GAN-Based Completion under Noisy and Incomplete Data
par: Gokcen, Alpaslan, et autres
Publié: (2025)

SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
par: Zhang, Heyi, et autres
Publié: (2025)

A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing
par: Gibert, Daniel, et autres
Publié: (2024)

Local Data Quantity-Aware Weighted Averaging for Federated Learning with Dishonest Clients
par: Wu, Leming, et autres
Publié: (2025)

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation
par: Herath, Charuka, et autres
Publié: (2025)