Machine learning (ML) models have been widely applied to various applications, including
image classification, text generation, audio recognition, and graph data analysis. However …

Federated learning (FL) is a kind of distributed machine learning framework, where the
global model is generated on the centralized aggregation server based on the parameters of …

Sixth generation (6G) enabled edge intelligence opens up a new era of Internet of
everything and makes it possible to interconnect people-devices-cloud anytime, anywhere …

Over the recent years, with the increasing adoption of Federated Learning (FL) algorithms
and growing concerns over personal data privacy, Privacy-Preserving Federated Learning …

With rapid growth in data volume generated from different industrial devices in IoT, the
protection for sensitive and private data in data sharing has become crucial. At present …

In this article, we present a comprehensive study with an experimental analysis of federated
deep learning approaches for cyber security in the Internet of Things (IoT) applications …

Over the last decade, smart cities (SC) have been developed worldwide. Implementing big
data and the internet of things improves the monitoring and integration of different …

As the 5G communication networks are being widely deployed worldwide, both industry and
academia have started to move beyond 5G and explore 6G communications. It is generally …

The individual and integration use of the Internet of Things (IoT), Information-Centric
Networking (ICN), and Federated Learning (FL) have recently been used in several network …

Federated learning faces many security and privacy issues. Among them, poisoning attacks
can significantly impact global models, and malicious attackers can prevent global models …