# Use Case Based Blended Teaching of IIoT Cybersecurity in the Industry 4.0 Era
## 1 Introduction  
Industry 4.0 is a concept that sets the foundations for evolving traditional factories to become smarter. Such an evolution is aimed at optimizing process efficiency and flexibility through the application of the latest technologies [1, 2]. Industry 4.0 foundations are similar to the ones suggested by other paradigms and initiatives, like Industrial Internet of Things (IIoT) [3], Internet Plus [4] or Made in China 2025 [5]. The most relevant technologies involved in Industry 4.0 are depicted in Figure 1 and include, among others, Augmented/Mixed/Virtual Reality (AR/MR/VR) [6, 7], integration systems [8], simulation software [9], additive manufacturing [10], Industrial Cyber-Physical Systems (ICPS) [11], Big Data [12], industrial autonomous machines like robots [13], Automated Guided Vehicles (AGVs) [14] and Unmanned Aerial Vehicles (UAVs) [15]. In addition, other recent technologies like blockchain [16] have been considered for creating autonomous decentralized industrial systems. Such enabling technologies allow for creating highlyconnected factories that often rely on cloud-centered architectures and, increasingly, on novel decentralized fog and edge computing architectures [17; 18]. The dashed lines that connected the different Industry 4.0 technologies in Figure 1 indicate the other technologies they rely on. For instance, Cyber-Physical Systems (CPSs) rely on IIoT devices and Big Data analysis in order to provide true Industry 4.0 applications. Such dashed lines in Figure 1 show that the different Industry 4.0 technologies have two main dependencies: cybersecurity and IIoT. The former is related to the need for providing robust and reliable factories, while the second one demonstrates the increasing dependence on IIoT devices like Programmable Logic Controllers (PLCs), industrial machinery, tools or communications gateways, which can be connected to internal LANs or to the Internet so as to monitor and to interact with them. Thus, IIoT devices are essential for industrial fields like agriculture [19; 20], healthcare [21] or heavy industries [22]. The problem is that many IIoT devices are in practice insecure due to weak security implementations or to the lack of a proper security configuration. Part of such an insecurity is related to certain hardware design requirements (e.g., many IIoT devices rely on batteries or are constrained in terms of memory or computational power), which prevent them from implementing complex security mechanisms (e.g., Rivest-Shamir-Adleman (RSA) [23] or Elliptic Curve Cryptography (ECC) [24]) that demand a relevant amount of resources [25]. In addition, IIoT firmware can have software bugs that in many cases are not easy to fix (e.g., they may involve replacing the hardware or require performing specific firmware update procedures). The previously mentioned security problems are essentially related to neglecting cybersecurity from the IIoT device design stage. In fact, security is often neglected by many IT university degrees, so, in general, graduates do not receive an intensive training on the diverse fields where security is key. This is the case of the industrial field, which, despite being critical, is barely studied from a cybersecurity point of view. In addition, there is a growing interest in blended or hybrid teaching models. Such models include a mix of traditional face-to-face instruction and ordinary classroom learning with online and  
Figure 1: Main Industry 4.0 technologies and their dependencies. remote learning and projects to engage students in the learning process. Specifically, flipped classroom is a pedagogical blended learning approach focused on student engagement and active learning.