This paper introduces a dynamic, proactive cyber risk assessment methodology that combines internal and external data, converting qualitative inputs into quantitative measures within a Bayesian network. Using the Exploit Prediction Scoring System, it dynamically estimates attack success probabilities and asset impact, validated through a Supervisory Control and Data Acquisition (SCADA) environment case study.
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