The recent developments in the research area of cyber-physical systems (CPS) and autonomous vehicles have seen significant advancements in the fields of anomaly detection, cyber threat intelligence, and process mining. The focus has been on enhancing security and adaptability in these systems to address emerging threats and operational complexities. Anomaly detection has seen innovative approaches, particularly in teleoperated driving systems, where physics-based context-aware systems are being developed to detect false data injection attacks. These systems leverage real-world data to model and assess risks, providing a robust defense mechanism against malicious activities. Cyber threat intelligence has also advanced with the creation of specialized datasets and frameworks for modeling and analyzing cyber threats in autonomous vehicles. These resources enable proactive security defense by extracting and analyzing threat information, thereby facilitating a more informed and responsive security posture. Additionally, process mining is evolving towards object-centric approaches, with new standards and models being proposed to simplify data exchange and enhance the understanding of complex processes. This shift is crucial for the development of more efficient and adaptable information systems, particularly in the context of software product lines and flexible process variant binding. Overall, the field is moving towards more integrated, adaptive, and secure systems that can better handle the dynamic and often adversarial environments they operate in.