PARC was awarded a two-year, $3.5 million contract with the Department of Defense. Developed via PARC’s open innovation model aimed at commercializing emerging technology to proactively identify internal threats, this technology will first be developed for the U.S. government, but the core technology has the potential to be deployed commercially to help stop corporate insider threats, says PARC.
PARC is involved in spearheading the Graph Learning for Anomaly Detection using Psychological Context (GLAD-PC) project, which aims to provide automatic, proactive threat identification and ranking from large-scale behavioral and information-network datasets.
PARC has selected a number of subcontractors for this particular government project. On the psychological context modeling and analysis side, HumRRO is providing expertise in dynamic psychological modeling. On the graph learning side, NASA Ames Research Center is providing unique capabilities in graph structure analysis and anomaly detection. Semantic information network analysis and graph theory expert, Stony Brook University is also contributing to the project.