Theoretical Insights into Leveraging Machine Learning for Dynamic Cyber Risk Assessment and Enhancing Cyber Situational Awareness in SMEs

Small and mid-sized enterprises (SMEs) play a role in economies, but they are increasingly challenged to protect their digital assets. Unlike companies that have specialised cybersecurity teams and resources, SMEs often lack the knowledge and infrastructure needed to defend themselves against cyber threats. This vulnerability highlights the importance of taking an approach to cybersecurity which allows SMEs to stay vigilant about risks and the changing threat landscape. This theoretical paper investigates how AI (Artificial Intelligence) can enhance cyber situational awareness (CSA) and enable dynamic cyber risk assessment (DCRA) in SMEs. It establishes the criticality of CSA for effective cybersecurity measures, discusses existing CSA approaches and their limitations in the SME context, and explores the concept of cyber risk assessment and its challenges for SMEs, highlighting the need for dynamic approaches. This critical insight highlights the importance of adaptability in the cyber environment and enlightens the audience on its significance. In detail, the paper presents a literature review that delves into the role of AI in cybersecurity, highlighting its advantages for resource-constrained SMEs. It explores how AI can be harnessed to enhance DCRA and improve CSA. In conclusion, the paper summarises the essential findings and highlights the transformative potential of AI in empowering SMEs to take a proactive stance in managing their cybersecurity posture.