Kurt Boberg / how-to-measure-anything-in-cybersecurity-risk-with-julia · GitLab

ONE SENTENCE SUMMARY: “How to Measure Anything in Cybersecurity Risk with Julia” explores quantitative methods to assess cybersecurity risks using Julia programming.
MAIN POINTS:
Demonstrates applying quantitative risk analysis to cybersecurity using the Julia programming language.
Emphasizes that anything in cybersecurity risk can be measured, even with uncertainty.
Advocates for replacing qualitative risk scores with data-driven, probabilistic models.
Introduces Monte Carlo simulations to estimate risk distributions and outcomes.
Uses Julia for its speed, flexibility, and suitability for numerical computing.
Encourages starting with available data, no matter how incomplete, to begin measuring risk.
Explains how to build simple models that can evolve with better data over time.
Highlights the value of Expected Value of Information (EVI) in prioritizing measurements.
Provides examples and Julia code snippets to model various cybersecurity scenarios.
Suggests integrating measurement models into decision-making processes for better security investments.
TAKEAWAYS:
Cybersecurity risk can and should be measured quantitatively, not just qualitatively.
Julia is a powerful tool for building fast, flexible cybersecurity risk models.
Even uncertain or incomplete data can provide valuable insight when modeled correctly.
Monte Carlo simulations are effective for forecasting risk scenarios and outcomes.
Prioritizing what to measure using EVI enhances decision-making and resource allocation.