利用数字孪生检测和减轻开放式RAN中的对抗性机器学习

IF 5.5 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Wireless Communications Letters Pub Date : 2025-09-12 DOI:10.1109/lwc.2025.3609661

Seyed Ahmad Soleymani, Mohsen Eslamnejad, Mohammad Shojafar, Rahim Tafazolli

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Detecting and Mitigating Adversarial Machine Learning in Open RAN Using Digital Twin

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

IEEE Wireless Communications Letters Engineering-Electrical and Electronic Engineering

CiteScore

12.30

自引率

6.30%

发文量

481

期刊介绍： IEEE Wireless Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of wireless communications. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of wireless communication systems.