DP-FedCMRS: Privacy-Preserving Federated Learning Algorithm to Solve Heterogeneous Data

DP-FedCMRS: Privacy-Preserving Federated Learning Algorithm to Solve Heterogeneous Data

In federated learning, non-independently and non-identically distributed heterogeneous data on the clients can limit both the convergence speed and model utility of federated learning, and gradients can be used to infer original data, posing a threat to user privacy. To address these issues, this pa...

Full description

Saved in:

Bibliographic Details
Main Authors:	Yang Zhang, Shigong Long, Guangyuan Liu, Junming Zhang
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Series:	IEEE Access
Subjects:	Federated learning differential privacy non-IID data clustering
Online Access:	https://ieeexplore.ieee.org/document/10910083/
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning With Adaptive Quantization and Differential Privacy
by: Emre Ardic, et al.
Published: (2025-01-01)

FL-QNNs: Memory Efficient and Privacy Preserving Framework for Peripheral Blood Cell Classification
by: Meenakshi Aggarwal, et al.
Published: (2025-01-01)

Adding Data Quality to Federated Learning Performance Improvement
by: Ernesto Gurgel Valente Neto, et al.
Published: (2025-01-01)

FedNDA: Enhancing Federated Learning with Noisy Client Detection and Robust Aggregation
by: Tuan Dung Kieu, et al.
Published: (2025-07-01)

Client grouping and time-sharing scheduling for asynchronous federated learning in heterogeneous edge computing environment
by: Qianpiao MA, et al.
Published: (2023-11-01)

Intrusion detection method for IoT in heterogeneous environment
by: LIU Jing, et al.
Published: (2024-04-01)

FedDrip: Federated Learning With Diffusion-Generated Synthetic Image
by: Karin Huangsuwan, et al.
Published: (2025-01-01)

Federated Learning for Privacy-Preserving Employee Performance Analytics
by: Jay Barach
Published: (2025-01-01)

FedEmerge: An Entropy-Guided Federated Learning Method for Sensor Networks and Edge Intelligence
by: Koffka Khan
Published: (2025-06-01)

GuardianAI: Privacy-preserving federated anomaly detection with differential privacy
by: Abdulatif Alabdulatif
Published: (2025-07-01)

Blockchain-based privacy-preserving multi-tasks federated learning framework
by: Yunyan Jia, et al.
Published: (2024-12-01)

A privacy-preserving federated learning framework
by: Yang Dongning, et al.
Published: (2022-05-01)

FedG2L: a privacy-preserving federated learning scheme base on “G2L” against poisoning attack
by: Mengfan Xu, et al.
Published: (2023-12-01)

MEFL: Meta-Equilibrize Federated Learning for Imbalanced Data in IoT
by: Jialu Tang, et al.
Published: (2025-05-01)

Phase-Adaptive Federated Learning for Privacy-Preserving Personalized Travel Itinerary Generation
by: Xiaolong Chen, et al.
Published: (2025-06-01)

Privacy-Preserving Federated Class-Incremental Learning
by: Jue Xiao, et al.
Published: (2024-01-01)

Federated Learning for Cybersecurity: A Privacy-Preserving Approach
by: Edi Marian Timofte, et al.
Published: (2025-06-01)

Privacy preserving federated learning with convolutional variational bottlenecks
by: Daniel Scheliga, et al.
Published: (2025-05-01)

Shuffle Model of Differential Privacy: Numerical Composition for Federated Learning
by: Shaowei Wang, et al.
Published: (2025-02-01)

Privacy-preserving federated learning framework with dynamic weight aggregation
by: Zuobin YING, et al.
Published: (2022-10-01)

BPS-FL: Blockchain-Based Privacy-Preserving and Secure Federated Learning
by: Jianping Yu, et al.
Published: (2025-02-01)

A Novel Approach for Differential Privacy-Preserving Federated Learning
by: Anis Elgabli, et al.
Published: (2025-01-01)

Object Re-Identification Based on Federated Incremental Subgradient Proximal Optimization
by: Li Kang, et al.
Published: (2025-01-01)

Federated Learning for Human Pose Estimation on Non-IID Data via Gradient Coordination
by: Peng Ni, et al.
Published: (2025-07-01)

Federated learning for digital twin applications: a privacy-preserving and low-latency approach
by: Jie Li, et al.
Published: (2025-08-01)

A robust and personalized privacy-preserving approach for adaptive clustered federated distillation
by: Mai Shawkat, et al.
Published: (2025-04-01)

A Verifiable, Privacy-Preserving, and Poisoning Attack-Resilient Federated Learning Framework
by: Washington Enyinna Mbonu, et al.
Published: (2025-03-01)

FedSW-TSAD: SWGAN-Based Federated Time Series Anomaly Detection
by: Xiuxian Zhang, et al.
Published: (2025-06-01)

Randomized Quantization for Privacy in Resource Constrained Machine Learning at-the-Edge and Federated Learning
by: Ce Feng, et al.
Published: (2025-01-01)

Privacy-Preserving Detection of Tampered Radio-Frequency Transmissions Utilizing Federated Learning in LoRa Networks
by: Nurettin Selcuk Senol, et al.
Published: (2024-11-01)

Survey on incentive-driven federated learning: privacy and security
by: CHI Huanhuan, et al.
Published: (2025-06-01)

DualPFL: A Dual Sparse Pruning Method with Efficient Federated Learning for Edge-Based Object Detection
by: Shijin Song, et al.
Published: (2024-11-01)

Balancing Privacy and Performance: A Differential Privacy Approach in Federated Learning
by: Huda Kadhim Tayyeh, et al.
Published: (2024-10-01)

Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning
by: Xiyu Zhao, et al.
Published: (2025-01-01)

A Hybrid Brain Tumor Classification Using FL With FedAvg and FedProx for Privacy and Robustness Across Heterogeneous Data Sources
by: N. Sivakumar, et al.
Published: (2025-01-01)

Incentive scheme for federated learning based on zero-concentrated differential privacy
by: LI Mengqian, et al.
Published: (2025-01-01)

A privacy-preserving dependable deep federated learning model for identifying new infections from genome sequences
by: Sk. Tanzir Mehedi, et al.
Published: (2025-03-01)

Federated Learning for Real-Time Demand Response by Data Centers Toward Energy Efficiency and Privacy Preservation
by: Mohannad Alhazmi, et al.
Published: (2025-01-01)

Privacy-enhanced federated learning scheme based on generative adversarial networks
by: Feng YU, et al.
Published: (2023-06-01)

Federated Learning for Distributed IoT Security: A Privacy-Preserving Approach to Intrusion Detection
by: Chandu Gutti, et al.
Published: (2025-01-01)