Automated real-time multi-dimensional cybersecurity threat modeling

Abstract

A plurality of communicatively coupled, networked assets of an organization may be threatened or attacked by a cybersecurity attack or other form of attack. Control mechanisms may be installed and established to protect against specific cybersecurity attacks and other infiltrations. Machine learning and predictive analytics are used to more appropriately match specific attacks and threats against specific control mechanisms, accounting for dimensionality of control mechanisms. The matching of attack patterns and control mechanisms may use test scripts that operate on data pulled from the organization's systems of record. A factor analysis of information risk (FAIR) may be performed and visual threat models may be automatically generated that show the mapping between a threat actor, attack type, control environment including dimensionality, the targeted system, and the impact on the organization.