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DOE OSTI · 1871012

Synthetic Data and Graph Generation for Modeling Adversarial Activity (Final Project Report)

Purohit, Sumit·Mackey, Patrick S.·Cottam, Joseph A.·Dunning, Madelyn P.·Chin, George
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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.

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Purohit, Sumit, Mackey, Patrick S., Cottam, Joseph A., Dunning, Madelyn P., Chin, George. 2022-02-01. Synthetic Data and Graph Generation for Modeling Adversarial Activity (Final Project Report). https://doi.org/10.2172/1871012

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