AI-based Cybersecurity for a Sustainable Digital Industry: Systematic Literature Review and Future Research Directions

The adoption of artificial intelligence (AI) to ensure sustainable cybersecurity practices is a major challenge in the era of Industry 4.0. AI techniques can classify and detect the huge number of cyber-attacks affecting modern industrial systems due to their adaptability and predictability, offering speed of classification, discovery of hidden patterns, and increased accuracy. However, the current literature shows a significant gap in analysing the relationship between AI-based cyber risk assessment and sustainability pillars (i.e., economic, social, and environmental) in modern industrial contexts. To fill this gap, this study explores the opportunities that AI techniques applied to cyber risk assessment can offer in terms of sustainability in the context of Industrial Internet of Things (IIoT). Specifically, a Systematic Literature Review (SLR) is conducted for the purpose of exploring the following four areas: (i) the definitions of sustainable cybersecurity and green cybersecurity in the industrial context; (ii) the AI techniques adopted for risk assessment, from a sustainability perspective; (iii) the industries involved; and (iv) the sustainability benefits of implementing AI technologies for cyber risk assessment. Following this analysis, an original tabular outline is created and validated by domain experts. It brings together evidence from the literature to facilitate understanding of the interplay between sustainability and cybersecurity and highlight the contribution that AI can bring not only to cyber risk assessment, but also to sustainability pillars, laying the groundwork for interesting future research directions.