Explore Patterns to Detect Sybil Attack during Federated Learning in Mobile Digital Twin Network-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Explore Patterns to Detect Sybil Attack during Federated Learning in Mobile Digital Twin Network

Published:2024-06-09 Issue: Volume:30 Page:3969-3974
ISSN:
Container-title:ICC 2024 - IEEE International Conference on Communications
language:
Short-container-title:

Author:

Zhang Wenmiao¹,Yu Chong²,Meng Zhenyu¹,Shen Shuaiqi³,Zhang Kuan¹

Affiliation:

1. University of Nebraska-Lincoln,Department of Electrical and Computer Engineering,Lincoln,NE,USA

2. University of Cincinnati,Department of Computer Science,Cincinnati,OH,USA

3. University of Wisconsin-Milwaukee,Department of Electrical Engineering,Milwaukee,WI,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10622104/10622158/10622975.pdf?arnumber=10622975

Reference25 articles.

1. Cloud-Edge-Client Collaborative Learning in Digital Twin Empowered Mobile Networks

2. Digital Twin Enhanced Federated Reinforcement Learning With Lightweight Knowledge Distillation in Mobile Networks

3. Digital Twins Enabled On-Demand Matching for Multi-Task Federated Learning in HetVNets

4. Efficient Multi-Layer Stochastic Gradient Descent Algorithm for Federated Learning in E-health

5. Energy-Aware Device Scheduling for Joint Federated Learning in Edge-assisted Internet of Agriculture Things

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP