Cover Image

Coded Robust Aggregation for Distributed Learning under Byzantine Attacks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Chengxi, Xiao, Ming, Skoglund, Mikael
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive Coded Federated Learning: Privacy Preservation and Straggler Mitigation
by: Li, Chengxi, et al.
Published: (2024)

Attacking Byzantine Robust Aggregation in High Dimensions
by: Choudhary, Sarthak, et al.
Published: (2023)

Federated Learning Resilient to Byzantine Attacks and Data Heterogeneity
by: Zuo, Shiyuan, et al.
Published: (2024)

Rethinking Byzantine Robustness in Federated Recommendation from Sparse Aggregation Perspective
by: Zhang, Zhongjian, et al.
Published: (2025)

FedCAP: Robust Federated Learning via Customized Aggregation and Personalization
by: Li, Youpeng, et al.
Published: (2024)

Privacy-Preserving Aggregation for Decentralized Learning with Byzantine-Robustness
by: Ghavamipour, Ali Reza, et al.
Published: (2024)

Robust and Reliable Early-Stage Website Fingerprinting Attacks via Spatial-Temporal Distribution Analysis
by: Deng, Xinhao, et al.
Published: (2024)

Structure-Aware Distributed Backdoor Attacks in Federated Learning
by: Jian, Wang, et al.
Published: (2026)

Crypto Miner Attack: GPU Remote Code Execution Attacks
by: Szabo, Ariel, et al.
Published: (2025)

BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning
by: Liu, Yi, et al.
Published: (2024)

Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings
by: Arazzi, Marco, et al.
Published: (2025)

AdaBFL: Multi-Layer Defensive Adaptive Aggregation for Bzantine-Robust Federated Learning
by: Tang, Zehui, et al.
Published: (2026)

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning
by: Chen, Depeng, et al.
Published: (2024)

On the Robustness of Bayesian Neural Networks to Adversarial Attacks
by: Bortolussi, Luca, et al.
Published: (2022)

Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning
by: Shan, Junjie, et al.
Published: (2024)

Fair Finetuning Mitigates Distribution Inference Attacks
by: Naidu, Rakshit
Published: (2026)

Coding-Enforced Resilient and Secure Aggregation for Hierarchical Federated Learning
by: Weng, Shudi, et al.
Published: (2026)

A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments
by: Zhao, Kaixiang, et al.
Published: (2025)

Buffered Asynchronous Secure Aggregation for Cross-Device Federated Learning
by: Wang, Kun, et al.
Published: (2024)

Byzantine-Robust Federated Learning: An Overview With Focus on Developing Sybil-based Attacks to Backdoor Augmented Secure Aggregation Protocols
by: Deshmukh, Atharv
Published: (2024)

Data Overvaluation Attack and Truthful Data Valuation in Federated Learning
by: Zheng, Shuyuan, et al.
Published: (2025)

Disttack: Graph Adversarial Attacks Toward Distributed GNN Training
by: Zhang, Yuxiang, et al.
Published: (2024)

Feature Inference Attack on Shapley Values
by: Luo, Xinjian, et al.
Published: (2024)

The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of Triggers
by: Mengara, Orson
Published: (2024)

LoBAM: LoRA-Based Backdoor Attack on Model Merging
by: Yin, Ming, et al.
Published: (2024)

Privacy Auditing of Multi-domain Graph Pre-trained Model under Membership Inference Attacks
by: Luo, Jiayi, et al.
Published: (2025)

Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks
by: Abbahaddou, Yassine, et al.
Published: (2024)

Personalized Federated Learning with Adaptive Feature Aggregation and Knowledge Transfer
by: Yin, Keting, et al.
Published: (2024)

FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
by: Lee, Younghan, et al.
Published: (2024)

Edit Distance Robust Watermarks via Indexing Pseudorandom Codes
by: Golowich, Noah, et al.
Published: (2024)

A Study on Semi-Supervised Detection of DDoS Attacks under Class Imbalance
by: Hallaji, Ehsan, 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)

How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and Transformers
by: Zhang, Guangsheng, et al.
Published: (2022)

Can Adversarial Code Comments Fool AI Security Reviewers -- Large-Scale Empirical Study of Comment-Based Attacks and Defenses Against LLM Code Analysis
by: Thornton, Scott
Published: (2026)

BACKTIME: Backdoor Attacks on Multivariate Time Series Forecasting
by: Lin, Xiao, et al.
Published: (2024)

ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning
by: Xu, Zhangchen, et al.
Published: (2024)

Multi-Agent Reinforcement Learning for Assessing False-Data Injection Attacks on Transportation Networks
by: Eghtesad, Taha, et al.
Published: (2023)

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
by: Liang, Zi, et al.
Published: (2025)

Learning to Defend by Attacking (and Vice-Versa): Transfer of Learning in Cybersecurity Games
by: Malloy, Tailia, et al.
Published: (2023)

zkFL: Zero-Knowledge Proof-based Gradient Aggregation for Federated Learning
by: Wang, Zhipeng, et al.
Published: (2023)