Industry 4.0 has revolutionized process innovation while facilitating and encouraging many new possibilities. The objective of Industry 4.0 is the radical enhancement of productivity, a goal that presupposes the integration of Operational Technology (OT) networks with Information Technology (IT) networks, which were hitherto isolated. This disruptive approach is enabled by adopting several emerging technologies in Enterprise processes. In this manuscript, we discuss what we believe to be one of the main challenges preventing the full employment of Industry 4.0, namely, the integration of Operation Technology networking and Information Technology networking. We discuss the technical challenges alongside the potential tools while providing a state-of-the-art use case scenario. We showcase a possible solution based on the Asset Administration Shell approach, referring to the use case of camera synchronization for collaborative tasks.

The ubiquitous diffusion of connected devices in every context of the daily life of citizens, public bodies, and companies is stimulating the creation of new applications that require very high wireless communication performances. To fulfill this need, the sixth generation of communication standards (6G) is planned to roll out by 2030. While structuring this new standard, it is crucial to take into account the security aspects given the impact of the technologies that will rely on its reliability and resiliency. In this paper, we provide an overview of the technologies that will be used in 6G to achieve the required functional goals for the development of key applications. Then, we proceed to discuss the threats and the solutions to make the communications infrastructure secure and reliable, and finally, we elaborate on the concept of how to achieve trust in this scenario.

Nowadays, as the cyber-threat landscape is evolving and digital assets are proliferating and becoming more and more interconnected with the internet and heterogeneous devices, it is fundamental to be able to obtain a sensible measure of the security of devices, networks, and systems. Industrial cyber–physical systems (ICPSs), in particular, can be exposed to high operational risks that entail damage to revenues, assets, and even people. A way to overcome the open question of measuring security is with the use of security metrics. With metrics it is possible to rely on proven indicators that benchmark systems, identify vulnerabilities, and show practical data to assess the risk. However, security metrics are often proposed with specific contexts in mind, and a set of them specifically crafted for ICPSs is not explicitly available in the literature. For this reason, in this work, we analyze the current state of the art in the selection of security metrics and we propose a systematic methodology to gather, filter, and validate security metrics. Then, we apply the procedure to the ICPS domain, gathering almost 300 metrics from the literature, analyzing the domain to identify the properties useful to filter the metrics, and applying a validation framework to assess the validity of the filtered metrics, obtaining a final set capable of measuring the security of ICPSs from different perspectives.

The correct and efficient measurement of security properties is key to the deployment of effective cyberspace protection strategies. In this work, we propose GRAPH4, which is a system that combines different security metrics to design an attack detection approach that leverages the advantages of modern network architectures. GRAPH4 makes use of attack graphs that are generated by the control plane to extract a view of the network components requiring monitoring, which is based on the specific attack that must be detected and on the knowledge of the complete network layout. It enables an efficient distribution of security metrics tasks between the control plane and the data plane. The attack graph is translated into network rules that are subsequently installed in programmable nodes in order to enable alerting and detecting network anomalies at a line rate. By leveraging data plane programmability and security metric scores, GRAPH4 enables timely responses to unforeseen conditions while optimizing resource allocation and enhancing proactive defense. This paper details the architecture of GRAPH4, and it provides an evaluation of the performance gains it can achieve.

Industrial digitalization is moving from Industry 4.0 toward Industry 5.0’s emphasis on resilience, human-centric operation, and sustainability. This shift is enabled by the convergence of Operational Technology and Information Technology, but this integration also broadens the exposure of industrial infrastructures to cyber threats targeting communication integrity and process continuity. Mitigating these risks requires network control that is both programmable and aware of each asset’s operational context. However, there is still a lack of operational interfaces that translate the semantics of industrial assets into programmable, runtime-enforceable network behavior. In this paper, following a Design Science Research methodology, we introduce an asset-aware, closed-loop network control abstraction in which the industrial network itself is modeled as a managed asset through Asset Administration Shells. Asset state, lifecycle phase, and operational intent are translated into network policies enforced at runtime on programmable data planes, while in-network telemetry is exposed at the asset level and correlated with operational metrics. We validate the abstraction on a hybrid testbed that combines virtualized components with industrial-grade hardware and virtualized 5G connectivity, through three security-oriented use cases: (i) asset-driven customization of forwarding policies; (ii) human-centric secure maintenance with controlled remote access over 5G; and (iii) anomaly detection and isolation based on cross-layer telemetry correlation. The results show that asset-level operations can drive programmable network enforcement and make network telemetry available at the asset layer. Finally, the work outlines a first step toward standardizing network-oriented asset submodels by separating control-plane operations from data-plane state and telemetry.