Cover Image

Boosting Communication Efficiency of Federated Learning's Secure Aggregation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nazemi, Niousha, Tavallaie, Omid, Chen, Shuaijun, Zomaya, Albert Y., Holz, Ralph
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ACCESS-FL: Agile Communication and Computation for Efficient Secure Aggregation in Stable Federated Learning Networks
by: Nazemi, Niousha, et al.
Published: (2024)

Analysis of DNS Dependencies and their Security Implications in Australia: A Comparative Study of General and Indigenous Populations
by: Nazemi, Niousha, et al.
Published: (2024)

RBLA: Rank-Based-LoRA-Aggregation for Fine-tuning Heterogeneous Models in FLaaS
by: Chen, Shuaijun, et al.
Published: (2024)

SHFL: Secure Hierarchical Federated Learning Framework for Edge Networks
by: Tavallaie, Omid, et al.
Published: (2024)

AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning
by: Chen, Shuaijun, et al.
Published: (2024)

Federated Learning as a Service for Hierarchical Edge Networks with Heterogeneous Models
by: Gao, Wentao, et al.
Published: (2024)

Secure Aggregation in Federated Learning using Multiparty Homomorphic Encryption
by: Hosseini, Erfan, et al.
Published: (2025)

Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning
by: Behnia, Rouzbeh, et al.
Published: (2023)

Breaking Secure Aggregation: Label Leakage from Aggregated Gradients in Federated Learning
by: Wang, Zhibo, et al.
Published: (2024)

Armadillo: Robust Single-Server Secure Aggregation for Federated Learning with Input Validation
by: Ma, Yiping, et al.
Published: (2025)

Per-element Secure Aggregation against Data Reconstruction Attacks in Federated Learning
by: Suimon, Takumi, et al.
Published: (2025)

FBChain: A Blockchain-based Federated Learning Model with Efficiency and Secure Communication
by: Li, Yang, et al.
Published: (2023)

Secure Stateful Aggregation: A Practical Protocol with Applications in Differentially-Private Federated Learning
by: Ball, Marshall, et al.
Published: (2024)

λ-SecAgg: Partial Vector Freezing for Lightweight Secure Aggregation in Federated Learning
by: Zhang, Siqing, et al.
Published: (2023)

Convergence Analysis of Aggregation-Broadcast in LoRA-enabled Distributed Fine-Tuning
by: Chen, Xin, et al.
Published: (2025)

Enhanced Security and Efficiency in Blockchain with Aggregated Zero-Knowledge Proof Mechanisms
by: Kuznetsov, Oleksandr, et al.
Published: (2024)

Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning
by: Zhang, Yiwei, et al.
Published: (2024)

Fluent: Round-efficient Secure Aggregation for Private Federated Learning
by: Li, Xincheng, et al.
Published: (2024)

TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning
by: Xu, Runhua, et al.
Published: (2025)

FederBoost: Private Federated Learning for GBDT
by: Tian, Zhihua, et al.
Published: (2020)

Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications
by: Taiello, Riccardo, et al.
Published: (2024)

On Using Secure Aggregation in Differentially Private Federated Learning with Multiple Local Steps
by: Heikkilä, Mikko A.
Published: (2024)

Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation
by: Yang, Kun, et al.
Published: (2025)

When Secure Aggregation Falls Short: Achieving Long-Term Privacy in Asynchronous Federated Learning for LEO Satellite Networks
by: Elmahallawy, Mohamed, et al.
Published: (2025)

Efficiently Achieving Secure Model Training and Secure Aggregation to Ensure Bidirectional Privacy-Preservation in Federated Learning
by: Yang, Xue, et al.
Published: (2024)

Camel: Communication-Efficient and Maliciously Secure Federated Learning in the Shuffle Model of Differential Privacy
by: Xu, Shuangqing, et al.
Published: (2024)

Hyperparameter Optimization for SecureBoost via Constrained Multi-Objective Federated Learning
by: Kang, Yan, et al.
Published: (2024)

CCA-Secure Key-Aggregate Proxy Re-Encryption for Secure Cloud Storage
by: Chen, Wei-Hao, et al.
Published: (2024)

Flamingo: Multi-Round Single-Server Secure Aggregation with Applications to Private Federated Learning
by: Ma, Yiping, et al.
Published: (2023)

Efficient Privacy-Preserving Cross-Silo Federated Learning with Multi-Key Homomorphic Encryption
by: Omar, Abdullah Al, et al.
Published: (2025)

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

Voltran: Unlocking Trust and Confidentiality in Decentralized Federated Learning Aggregation
by: Wang, Hao, et al.
Published: (2024)

AdRo-FL: Informed and Secure Client Selection for Federated Learning in the Presence of Adversarial Aggregator
by: Hossain, Md. Kamrul, et al.
Published: (2025)

Privacy-Preserving Data Aggregation Techniques for Enhanced Efficiency and Security in Wireless Sensor Networks: A Comprehensive Analysis and Evaluation
by: Rastogi, Ayush, et al.
Published: (2024)

Empirical Security Analysis of Software-based Fault Isolation through Controlled Fault Injection
by: Bars, Nils, et al.
Published: (2025)

Lotto: Secure Participant Selection against Adversarial Servers in Federated Learning
by: Jiang, Zhifeng, et al.
Published: (2024)

DisAgg: Distributed Aggregators for Efficient Secure Aggregation in Federated Learning
by: Mehmood, Haaris, et al.
Published: (2026)

Improving Efficiency in Federated Learning with Optimized Homomorphic Encryption
by: Yang, Feiran
Published: (2025)

FedGT: Identification of Malicious Clients in Federated Learning with Secure Aggregation
by: Xhemrishi, Marvin, et al.
Published: (2023)

Unveiling the Security Risks of Federated Learning in the Wild: From Research to Practice
by: Chen, Jiahao, et al.
Published: (2026)