Secure Federated Learning for Cognitive Radio Sensing

被引：16

作者：

Wasilewska, Malgorzata ^{[1
]}

Bogucka, Hanna ^{[2
]}

Poor, H. Vincent ^{[3
]}

机构：

[1] Poznan Univ Tech, Poznan, Poland

[2] Inst Radiocommunicat PUT, Vasant Kunj, India

[3] Princeton Univ, Princeton, NJ USA

来源：

IEEE COMMUNICATIONS MAGAZINE | 2023年 / 61卷 / 03期

关键词：

Federated learning; Cognitive radio; Spread spectrum management;

D O I：

10.1109/MCOM.001.2200465

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This article considers reliable and secure spectrum sensing (SS) based on federated learning (FL) in the cognitive radio (CR) environment. Motivation, architectures, and algorithms of FL in SSare discussed. Security and privacy threats on these algorithms are overviewed, along with possible countermeasures to such attacks. Some illustrative examples are also provided, with design recommendations for FL-based SS in future CRs.

引用

页码：68 / 73

页数：6

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