A new industrial production model based on digitalization, system interconnection, virtualization and data exploitation, has emerged. Upgrade of production processes towards this Industry 4.0 model is one of the critical challenges for the industrial sector and, consequently, the training of students and professionals has to address these new demands. To carry out this task, it is essential to develop educational tools that allow students to interact with real equipment that implements, in an integrated way, new enabling technologies, such as connectivity with standard protocols, storage and data processing in the cloud, machine learning, digital twins and industrial cybersecurity measures. For that reason, in this work, we present an educational environment on Industry 4.0 that incorporates these technologies reproducing realistic industrial conditions. This environment includes cutting-edge industrial control system technologies, such as an industrial firewall and a virtual private network (VPN) to strengthen cybersecurity, an Industrial Internet of Things (IIoT) gateway to transfer process information to the cloud, where it can be stored and analyzed, and a digital twin that virtually reproduces the system. A set of hands-on tasks for an introductory automation course have been proposed, so that students acquire a practical understanding of the enabling technologies of Industry 4.0 and of its function in a real automation. This course has been taught in a master’s degree and students have assessed its usefulness by means of an anonymous survey. The results of the educational experience have been useful both from the students’ and faculty’s viewpoint.

Environment for Education on Industry 4.0

Industrial Control Systems (ICS), which include Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), and Programmable Logic Controllers (PLC), play a crucial role in managing and regulating industrial processes. However, ensuring the security of these systems is of utmost importance due to the potentially severe consequences of cyber attacks. This article presents an overview of ICS security, covering its components, protocols, industrial applications, and performance aspects. It also highlights the typical threats and vulnerabilities faced by these systems. Moreover, the article identifies key factors that influence the design decisions concerning control, communication, reliability, and redundancy properties of ICS, as these are critical in determining the security needs of the system. The article outlines existing security countermeasures, including network segmentation, access control, patch management, and security monitoring. Furthermore, the article explores the integration of machine learning techniques to enhance the cybersecurity of ICS. Machine learning offers several advantages, such as anomaly detection, threat intelligence analysis, and predictive maintenance. However, combining machine learning with other security measures is essential to establish a comprehensive defense strategy for ICS. The article also addresses the challenges associated with existing measures and provides recommendations for improving ICS security. This paper becomes a valuable reference for researchers aiming to make meaningful contributions within the constantly evolving ICS domain by providing an in-depth examination of the present state, challenges, and potential future advancements.

Securing Industrial Control Systems: Components, Cyber Threats, and Machine Learning-Driven Defense Strategies

With the introduction of advanced monitoring and communication technologies, the legacy power system is evolving toward fully digitalized smart grid. The IEC 61850 standards have emerged as popular standards for automation of the power grid systems. However, modernization of the power grid has an unintended consequence of increased vulnerability to cyber-attacks. Among the emerging cyber threats, in this article we focus on false data injection attacks against generators in IEC 61850 compliant systems since this subject is not yet intensively studied in literature. We conduct the study on attack vectors against automated control logic for parallel generators and their feasibility, and conduct simulation experiments to demonstrate the attack impact. Based on the identified attack vectors, we further propose an efficient message authentication scheme. We investigate real-world control logic taken from the state-of-the-art smart grid test-bed for enumerating attack vectors. We further create virtual test-bed that is fully compliant to IEC 61850 standards for simulation study. The proposed message authentication schemes are implemented and intensively evaluated to demonstrate advantages over the other schemes. While effectively countering the identified attack vectors, the proposed message authentication scheme improves the latency by 16% compared to the scheme recommended in IEC 62351 standards. 

Analysis of False Data Injection Attacks Against Automated Control for Parallel Generators in IEC 61850-Based Smart Grid Systems

With the advent of Industry 4.0 , industries are requested to provide customisation of the products, with a high number of tailored features, which a pure robotic assembly line cannot provide. This suggests using a collaborative and flexible scenario together with the need for workflow modelling architectures. These can handle the communication and interaction among the actors of the workcell to improve the collaboration, making it more fluent, reliable, and able to correct workers’ oversights. Within this scenario, the main contribution of this paper is the introduction of a general library of atomic Predicates that can be combined with a first-order logic allowing to model general industrial assembly processes in human–robot collaboration. Such logics and Predicates allow to model and supervise the workflow, remaining hidden to the operator through an interface that intervenes only when errors have to be notified. The methodology has been validated on a complex collaborative assembly use case, requiring different tools and characterized by components of several sizes and shapes. Predicates have been mainly exploited to recognize human activities, allowing modelling and supervising the workflow. • Formalization of a library of predicates for human activity recognition. • Extension of an architecture to model and supervise assembly operations workflow. • Validation of the proposed methodology in a complex use case scenario. 

Workflow modelling for human-robot collaborative assembly operations

The wide deployment of Internet of Things (IoT) devices enables the controller to continuously collect massive volume data in automation systems, and makes it possible to make intelligent decisions based on machine learning techniques. In fact, data‐driven intelligent automation systems have been common in the industrial community. Nevertheless, how to effectively store the collected stream data and ensure their integrity is still challenging. To this end, the notion of verifiable data streaming (VDS) protocol, which enables a client to outsource the stream data to an untrusted server in a verifiable manner, was introduced. However, we argue that existing VDS protocols based on the chameleon authentication tree (CAT) are inefficient in the data update, since the whole CAT must be updated accordingly to avoid acute exposure of chameleon hashing. Thus, they are infeasible for intelligent automation systems that need to frequently update data. In this article, we first introduce a new primitive called double‐trapdoor chameleon hash tree (DCHT) based on the double‐trapdoor chameleon hash families, where each leaf of DCHT is calculated and fixed by using a double‐trapdoor chameleon hash family, making the entire DCHT always unchanged. Furthermore, we propose a novel VDS protocol based on the DCHT. Due to the distinctive properties of the underlying DCHT, the proposed VDS protocol has a constant update cost and more efficient than previous VDS protocols based on CAT. Besides, we prove that the proposed VDS protocol is secure in the standard model.

Verifiable data streaming with efficient update for intelligent automation systems

Programmable logic controllers (PLCs) are an established platform, widely used throughout industrial automation but poorly understood among researchers. This article gives an overview of the state of the practice, explaining why this settled technology persists throughout industry and presenting a critical analysis of the strengths and weaknesses of the dominant programming styles for today's PLC-based automation systems. We describe the software execution patterns that are standardized loosely in IEC 61131-3. We identify opportunities for improvements that would enable increasingly complex industrial automation applications while strengthening safety and reliability. Specifically, we propose deterministic, distributed programming models that embrace explicit timing, event-triggered computation, and improved security.

/pdf/programmable-logic-controllers-in-the-context-of-industry-4-3mmp45iqfn.pdf

Programmable Logic Controllers in the Context of Industry 4.0

GRAFCET is a powerful graphical modelling language and an international standard to specify the behavior of discrete event systems. One of the main advantages of GRAFCET compared to other specification languages is the description of distributed and nested program parts within a control application based on the hierarchical structures enclosing steps, partial-Grafcet and forcing orders. This contribution presents a meta-model based approach for GRAFCET specifications, including hierarchical structures. For this purpose, a suitable static GRAFCET meta-model has been defined. This model is the basis for both, a model-driven implementation of a graphical editor as well as a model-based GRAFCET syntax verification. This meta-model based approach has been made in consideration of the benefits of MDSD and the potential to expand the solution to other issues of formal methods in control system engineering. An integrated software solution is presented using the open-source environment Eclipse.

A meta-model based environment for GRAFCET specifications

A model-driven approach for transforming GRAFCET specification into PLC code including hierarchical structures

Method for monitoring an industrial installation, computer program, computer-readable medium and system

Opportunities for Industrial Control

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