Quantifying security risk is an important and yet difficult task in enterprise network risk management, critical for proactive mission assurance. Even though metrics exist for individual vulnerabilities, there is currently no standard way of aggregating such metrics. We developed a quantitative... See full abstract

Quantifying security risk is an important and yet difficult task in enterprise network risk management, critical for proactive mission assurance. Even though metrics exist for individual vulnerabilities, there is currently no standard way of aggregating such metrics. We developed a quantitative model that can be used to aggregate vulnerability metrics in an enterprise network, with a sound computation model. Our model produces quantitative metrics that measure the likelihood that breaches can occur within a given network configuration, taking into consideration the effects of all possible interplays between vulnerabilities. In order to validate the effectiveness scalability and accuracy) of this approach to realistic networks, we present the empirical study results of the approach on a number of system configurations. We use a real network as the test bed to demonstrate the utility of the approach, showing that the sound computation model is crucial for interpreting the metric result.
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