Critical Insight Purpose
To meet changing threats in an environment of limited data sets, strict privacy concerns and inherent bias.
As the severity and frequency of cyber and national security threats increase, leaders must decide which strategies, technologies will deliver the greatest risk reducing impact.
But to do so they need technologies that can:
- Detect the threat accurately
- Model the threat with confidence
- Monitor the threat continuously as it changes
- Quantify the Risk within agreed tolerance levels.
To meet these changing threats in an environment of limited data sets, strict privacy concerns and inherent bias, an underground architecture has been developed.
The architecture unifies a range of state-of-the-art AI models into a single, explainable Bayesian probabilistic framework to:
- Monitor, validate, and model multiple probabilistic risk factors (people-behaviours, roles, access, control effectiveness, value at risk) to quantify the risk threat.
Driven by the increasing availability of interconnected multi-modal information sources that enhances the capacity of novel probabilistic models to leverage context present in relational data, we have called our solution Critical Insight.
