Cyber-threat analyses using machine learning and prior observations

Abstract

A cyber-security analysis method uses machine learning (ML) technology to classify cyber-threat indicators, for example, as malicious or benign, by generating a threat score. The method includes receiving, at a compute device, a cyber-threat indicator (IUE) and associated verdicts from a set of sources. Augmenting the verdicts associated with the IUE with verdicts associated with at least one related indicator having a defined relationship with the IUE. The relationship between the IUE and the at least one related indicator can be operational, e.g., based on an administrative domain, or functional, e.g., based on a protocol specification. The cyber-threat score is generated for the IUE based on the ML model and the combined verdicts of the IUE and the at least one related indicator.