June 5, 2022
Report
Synthetic Data and Graph Generation for Modeling Adversarial Activity – Final Project Report
Abstract
The Data and Graph Generation for Modeling Adversary Activity (MAA) project developed a methodology along with scalable graph modeling and generation tools to produce realistic large-scale background activity graphs with embedded adversarial activity pathways. The technical report presents PNNL methodology, released datasets, lessons learned, and recommendations to develop graph analytic algorithms for structure-only and attributed knowledge graphs.Published: June 5, 2022