Towards Automating Design and Development of Inference Enterprise Models

James D. Lee, Shou Matsumoto, Abbas K. Zaidi, Kathryn B. Laskey

Abstract: In this paper, a process improvement approach, which provides automated assistance in designing and developing Inference Enterprise Models (IEM), is described. An IEM forecasts and evaluates the performance of the modeled enterprise and can be used to improve the operational quality of an enterprise making mission-focused inferences. As part of developing the IEM methodology, a team of researchers built several Inference Enterprise Models and acquired a breadth of knowledge in the domain of modeling insider threat detection systems. Although there are many different ways this type of inference enterprise can be modeled, there are common elements that are reused from case to case. We propose a solution for formalizing and reusing this IEM domain knowledge by developing an IEM Process Ontology and Workflow Generator.