Secure Federated Learning for Cognitive Radio Sensing

Malgorzata Wasilewska, Hanna Bogucka, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)68-73
Number of pages6
JournalIEEE Communications Magazine
Volume61
Issue number3
DOIs
StatePublished - Mar 1 2023

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Secure Federated Learning for Cognitive Radio Sensing'. Together they form a unique fingerprint.

Cite this