The fourth industrial revolution has significantly increased the adoption of Digital Twins
(DTs) across various sectors, including intelligent manufacturing, automation, logistics, and …

The explosive growth of Internet of Things (IoT) devices has led to escalating threats from
distributed denial of service (DDoS) attacks. Moreover, the scale and heterogeneity of IoT …

With the maturity of artificial intelligence (AI) technology, applications of AI in edge
computing will greatly promote the development of industrial technology. However, the …

Federated learning (FL) is considered a de facto standard for privacy preservation in AI
environments because it does not require data to be aggregated in some central place to …

Abstract In industry 4.0, Industrial Cyber–Physical Systems (ICPS) integrate industrial
machines with computer control and data analysis. Federated Learning (FL) improves this …

The fast evolutions of Internet of Things (IoT) technologies have been accelerating their
applicability in different sectors of life and becoming a pillar for sustainable development …

Virtual reality (VR), while enhancing user experiences, introduces significant privacy risks.
This paper reveals a novel vulnerability in VR systems that allows attackers to capture VR …

In recent years we have seen the emergence of new industrial paradigms such as Industry
4.0/5.0 or the Industrial Internet of Things (IIoT). As the use of these new paradigms …

The convergence of Federated learning (FL) and Edge computing (EC) has emerged as an
essential paradigm, particularly within the Industrial Internet of Things (IIoT) to enable the …

Federated Learning (FL) is a technique that can learn a global machine-learning model at a
central server by aggregating locally trained models. This distributed machine-learning …