The emergence of the Industrial Internet of Things (IIoT) can transform and improve industrial domain processes. This is achieved by IIoT’s ability to collect and process vast amounts of data using technology such as sensors. IIoT capabilities can improve the manufacturing processes of these sectors and contribute to the improved functioning of critical information infrastructure. In addition, current trends - such as the Fourth Industrial Revolution (4IR) - use IIoT to realise specific goals. While the emergence of IIoT systems does introduce many benefits, such as improved efficiency and sustainability, it can also introduce security concerns. These security concerns pose a significant threat to the industrial domain, including critical information infrastructures. The resulting threats emphasise the need to implement solutions to secure IIoT systems. The paper aims to discuss the emergence of IIoT and its cyber security issues within the context of critical information infrastructure. The research paper follows a theoretical research methodology to provide an improved understanding of the emergence of IIoT and its cyber security issues in critical information infrastructure. The paper contains an exhaustive discussion of what is IIoT. A discussion on where IIoT fits within the context of critical information infrastructure and its impact on 4IR is also highlighted in the paper. Due to the many vulnerabilities that IIoT systems can contain, the paper also discusses security concerns surrounding the emergence of IIoT. The security concerns make IIoT systems attractive targets for cyberattacks. Therefore, different approaches that can be applied to secure IIoT systems is also provided. Since IIoT capabilities can impact the critical information infrastructure of businesses and nations, the authors’ stance on how IIoT systems could transform the current understanding of critical information infrastructure is also discussed.

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This work presents AdaptiveSGA, a model for implementing Dynamic Difficulty Scaling through Adaptive Game AI via the Symbiotic Game Agent framework. The use of Dynamic Difficulty Balancing in modern computer games is useful when looking to improve the entertainment value of a game. Moreover, the Symbiotic Game Agent, as a framework, provides flexibility and robustness as a design principle for game agents. The work presented here leverages both the advantages of Adaptive Game AI and Symbiotic Game Agents to implement a robust, efficient and testable model for game difficulty scaling. The model is discussed in detail and is compared to the original Symbiotic Game Agent architecture. Finally, the paper describes how it was applied in simulated soccer. Finally, experimental results, which show that Dynamic Difficulty Balancing was achieved, are briefly analyzed.