Deep learning (DL) has been widely proposed for botnet attack detection in Internet of
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …

As an Internet of Things (IoT) technological key enabler, Wireless Sensor Networks (WSNs)
are prone to different kinds of cyberattacks. WSNs have unique characteristics, and have …

The industrial internet of things (IIoT) is an evolutionary extension of the traditional Internet of
Things (IoT) into processes and machines for applications in the industrial sector. The IIoT …

This review article looks at recent research on Federated Learning (FL) for Collaborative
Intrusion Detection Systems (CIDS) to establish a taxonomy and survey. The motivation …

In 2016, Google introduced the concept of Federated Learning (FL), enabling collaborative
Machine Learning (ML). FL does not share local data but ML models, offering applications in …

Wireless sensor networks are the core of the Internet of Things and are used in healthcare,
locations, the military, and security. Threats to the security of wireless sensor networks built …

Federated learning (FL) is an emerging subdomain of machine learning (ML) in a distributed
and heterogeneous setup. It provides efficient training architecture, sufficient data, and …

Federated Learning (FL) aims to train a globally shared model by employing local data
samples generated by data sources. The inherent heterogeneity of IoT environments, in …

The evolution of cybersecurity is undoubtedly associated and intertwined with the
development and improvement of artificial intelligence (AI). As a key tool for realizing more …

Quantum Federated Learning (QFL) recently becomes a promising approach with the
potential to revolutionize Machine Learning (ML). It merges the established strengths of …