Secure Federated Learning for Cognitive Radio Sensing

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.

Automated summary

This article explores reliable and secure spectrum sensing in cognitive radio using federated learning. It discusses the motivation, architectures, and algorithms of federated learning in spectrum sensing. It provides an overview of security and privacy threats on these algorithms and presents possible countermeasures. The article also includes illustrative examples and offers design recommendations for future cognitive radios.