System and method for summarization of complex cybersecurity behavioral ontological graph

A system comprising:

• one or more non-transitory computer readable media storing instructions;
• and
• one of more processors, operatively coupled to the one or more non-transitory computer readable media, to cause the system to execute the instructions to:
• monitor executed computational instructions to detect a potential threat;
• compare a query graph to an ontology graph;
• generate a result graph based at least in part upon the comparison;
• apply machine learning to data that is based at least in part upon at least a portion of the result graph,
• wherein applying machine learning to the data comprises generating a prompt based on at least a portion of the result graph, wherein the result graph is represented in a language format;
• generate a summary based at least in part upon the application of the machine learning;
• and
• display the summary, wherein the displayed summary is human readable.

One or more non-transitory computer readable media storing instructions that, when executed by one or more processors, cause the one or more processors to:

• monitor executed computational instructions to detect a potential threat;
• compare a query graph to an ontology graph;
• generate a result graph based at least in part upon the comparison;
• apply machine learning to data that is based at least in part upon at least a portion of the result graph,
• wherein applying machine learning to the data comprises generating a prompt based on at least a portion of the result graph, wherein the result graph is represented in a language format;
• generate a summary based at least in part upon the application of the machine learning;
• and
• display the summary, wherein the displayed summary is human readable.