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It is imperative that our field evolves common cyber-risk analysis practices beyond purely qualitative models and embraces data-driven methodologies. This session will tackle the challenges and supposed limitations of quantitative analysis head on by comparing two data-confidentiality scenarios. These scenarios appear similar on the surface, but quantitative analysis reveals meaningful differences.

Learning Objectives:
1: Debunk myths about the impossibility of applying quantitative analysis to cyber.
2: Learn from real-world examples of how common risk models hide meaningful differences between scenarios.
3: Gain approachable tools that can be used to analyze similar use cases in own environment.

Pre-Requisites:
Risk analysis, data analytics.