Generating information technology incident risk score narratives

Abstract

Techniques are described for enabling an application to automatically generate text narratives explaining risk scores assigned to risk objects. The application uses natural language generation (NLG) techniques to enable the automatic create text narratives providing context and explanation for risk scores. The described approaches use data from a variety of data sources (e.g., risk event indexes, correlation search data, attack framework data, etc.) to create compelling and useful explanations of the risk analysis associated with identified risk objects. These automatically generated text narratives can be readily presented in any number of different interfaces without the need for complex visualizations or user effort to derive the same information. The automatically created text narratives enable users to better understand the risk analysis for particular risk objects, obtain storylines detailing risk objects' activity patterns over time, and to better analyze, triage, and mitigate IT environment risks based on such information.