This self-paced e-learning course provides a comprehensive introduction to the FAIR Controls Analytics Model (FAIR-CAM), an extension of the FAIR standard that enables more precise and defensible analysis of control effectiveness in the context of cyber risk. Designed for risk analysts, cybersecurity professionals, and control owners, the course helps learners understand how to evaluate, model, and communicate the risk reduction value of controls with greater clarity and rigor.
Through seven structured chapters, participants will move from foundational concepts to the application of FAIR-CAM in real-world scenarios. The course bridges the gap between traditional control frameworks and a functional, quantifiable model of how controls impact risk. By the end of the course, learners will be equipped to incorporate FAIR-CAM into FAIR-based analyses and support more informed decision-making in cybersecurity governance.
By completing this course, learners will be able to:
Explain the core concepts of control physiology and how FAIR-CAM enhances traditional control frameworks
Identify and classify control functions across Loss Event, Variance Management, and Decision Support categories
Understand how controls influence key FAIR risk factors and how to represent these effects using Boolean logic
Evaluate control efficacy using measurable dimensions such as coverage, variance, and intended vs operational performance
Apply FAIR-CAM to real-world scenarios to assess, model, and improve control strategies in support of quantitative risk analysis
