Cover Image

Federated Learning Based Decentralized Adaptive Intelligent Transmission Protocol for Privacy Preserving 6G Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Ahmed, Ansar
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Privacy-Preserving Decentralized Federated Learning via Explainable Adaptive Differential Privacy
by: Piran, Fardin Jalil, et al.
Published: (2025)

Privacy-Preserving, Dropout-Resilient Aggregation in Decentralized Learning
by: Ghavamipour, Ali Reza, et al.
Published: (2024)

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

FedAdOb: Privacy-Preserving Federated Deep Learning with Adaptive Obfuscation
by: Gu, Hanlin, et al.
Published: (2024)

Privacy-Preserving Decentralized AI with Confidential Computing
by: Lee, Dayeol, et al.
Published: (2024)

Privacy-Preserving AI-Enabled Decentralized Learning and Employment Records System
by: Xu, Yuqiao, et al.
Published: (2026)

MedHE: Communication-Efficient Privacy-Preserving Federated Learning with Adaptive Gradient Sparsification for Healthcare
by: Yesmin, Farjana
Published: (2025)

PRSI: Privacy-Preserving Recommendation Model Based on Vector Splitting and Interactive Protocols
by: Cao, Xiaokai, et al.
Published: (2024)

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

Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning
by: Díaz, Judith Sáinz-Pardo, et al.
Published: (2026)

Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks
by: Dong, Wenhan, et al.
Published: (2024)

Decentralized Federated Learning: A Survey on Security and Privacy
by: Hallaji, Ehsan, et al.
Published: (2024)

Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning
by: Zhang, Xiaojin, et al.
Published: (2025)

A Privacy-Preserving Federated Learning Method with Homomorphic Encryption in Omics Data
by: Negoya, Yusaku, et al.
Published: (2025)

Bittensor Protocol: The Bitcoin in Decentralized Artificial Intelligence? A Critical and Empirical Analysis
by: Lui, Elizabeth, et al.
Published: (2025)

Towards Adaptive, Learning-Based Security in Decentralized Applications
by: Behfar, Stefan Kambiz, et al.
Published: (2023)

Zero-Knowledge Federated Learning: A New Trustworthy and Privacy-Preserving Distributed Learning Paradigm
by: Wang, Taotao, et al.
Published: (2025)

Towards Efficient Privacy-Preserving Machine Learning: A Systematic Review from Protocol, Model, and System Perspectives
by: Zeng, Wenxuan, et al.
Published: (2025)

AESP: A Human-Sovereign Economic Protocol for AI Agents with Privacy-Preserving Settlement
by: Wang, Jian Sheng
Published: (2026)

VFEFL: Privacy-Preserving Federated Learning against Malicious Clients via Verifiable Functional Encryption
by: Cai, Nina, et al.
Published: (2025)

FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
by: Ye, Pukang, et al.
Published: (2025)

FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users
by: Rahulamathavan, Yogachandran, et al.
Published: (2023)

Privacy-Preserving in Blockchain-based Federated Learning Systems
by: M., Sameera K., et al.
Published: (2024)

Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks
by: Scheliga, Daniel, et al.
Published: (2023)

Zero-Knowledge Audit for Internet of Agents: Privacy-Preserving Communication Verification with Model Context Protocol
by: Jing, Guanlin, et al.
Published: (2025)

Privacy-Preserving Federated Learning from Partial Decryption Verifiable Threshold Multi-Client Functional Encryption
by: Wang, Minjie, et al.
Published: (2025)

Decentralized AI-driven IoT Architecture for Privacy-Preserving and Latency-Optimized Healthcare in Pandemic and Critical Care Scenarios
by: Sammangi, Harsha, et al.
Published: (2025)

Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
by: Allana, Sonal, et al.
Published: (2025)

Unlocking Apple's Private Cloud Compute: An Analysis of Privacy-Preserving Artificial Intelligence
by: Dittmar, Yannik, et al.
Published: (2026)

Privacy-Preserving Federated Learning with Differentially Private Hyperdimensional Computing
by: Piran, Fardin Jalil, et al.
Published: (2024)

Privacy-Preserving Heterogeneous Federated Learning for Sensitive Healthcare Data
by: Xu, Yukai, et al.
Published: (2024)

Noiseless Privacy-Preserving Decentralized Learning
by: Biswas, Sayan, et al.
Published: (2024)

CADRE: Customizable Assurance of Data Readiness in Privacy-Preserving Federated Learning
by: Hiniduma, Kaveen, et al.
Published: (2025)

Towards Privacy-Preserving Data-Driven Education: The Potential of Federated Learning
by: Khalil, Mohammad, et al.
Published: (2025)

Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models
by: Yu, Sixing, et al.
Published: (2023)

Privacy-Preserving LLMs Routing
by: Wu, Xidong, et al.
Published: (2026)

A Quantization-based Technique for Privacy Preserving Distributed Learning
by: Colombo, Maurizio, et al.
Published: (2024)

BACSA: A Bias-Aware Client Selection Algorithm for Privacy-Preserving Federated Learning in Wireless Healthcare Networks
by: Yadav, Sushilkumar, et al.
Published: (2024)

An Adaptive Differential Privacy Method Based on Federated Learning
by: Wang, Zhiqiang, et al.
Published: (2024)

Secure and Privacy-Preserving Vertical Federated Learning
by: Jin, Shan, et al.
Published: (2026)