This article explores the integration of Uncertainty Quantification (UQ) techniques in cloud security and intrusion detection, emphasising the importance of enhancing model calibration through UQ methods. The discussion highlights several case studies and examples, illustrating the practical implications and benefits observed in real-world scenarios. Future research directions are identified, focusing on dynamic uncertainty modelling, adaptive risk management, privacy-preserving UQ, and multi-cloud environments. Unique insights are provided on the integration of UQ into Service Level Agreements (SLAs), proactive risk mitigation strategies, and human-centric UQ approaches, contributing to a more holistic understanding of UQ’s role in enhancing cloud security. These insights aim to address current limitations and suggest avenues for future research to leverage UQ in tackling emerging challenges in cloud computing security.