The field of cybersecurity is rapidly evolving, with a growing focus on developing innovative game-theoretic strategies to combat increasingly sophisticated threats. Recent research has explored the application of Bayesian optimization and Stackelberg games to improve the allocation of security resources and defenses. Notably, the development of frameworks for constructing realistic security game instances and the integration of dynamic Bayesian belief updates have shown promise in enhancing network security. Furthermore, studies have highlighted the importance of aligning cybersecurity requirements with technical frameworks, such as the Cyber Resilience Act, to ensure effective compliance and threat mitigation. Overall, the field is moving towards more adaptive and strategic approaches to cybersecurity, leveraging advances in game theory and machine learning to stay ahead of emerging threats. Noteworthy papers include: Adaptive Honeypot Allocation in Multi-Attacker Networks via Bayesian Stackelberg Games, which presents a novel framework for strategic honeypot allocation, and Consistent and Compatible Modelling of Cyber Intrusions and Incident Response, which demonstrates a new approach to integrating intrusion models with incident response playbooks.