This paper describes an approach for integrating sociological and technical models to develop more complete threat assessment. Current approaches to analyzing and addressing threats tend to focus on the technical factors. This paper addresses development of predictive models that encompass behavioral as well as these technical factors. Using improvised explosive device (IED) attacks as motivation, this model supports identification of intervention activities 'left of boom' as well as prioritizing attack modalities. We show how Bayes nets integrate social factors associated with IED attacks into general threat model containing technical and organizational steps from planning through obtaining the IED to initiation of the attack. The social models are computationally-based representations of relevant social science literature that describes human decision making and physical factors. When combined with technical models, the resulting model provides improved knowledge integration into threat assessment for monitoring. This paper discusses the construction of IED threat scenarios, integration of diverse factors into an analytical framework for threat assessment, indicator identification for future threats, and future research directions.

We present an observational case study in which we investigate and analyze the analytical processes of intelligence analysts. Participating analysts in the study carry out two scenarios where they organize and triage information, conduct intelligence analysis, report results, and collaborate with one another. Through a combination of scenario-based analysis, artifact analysis, role-playing, interviews, and participant observations, we explore the space and boundaries in which intelligence analysts work and operate. We also assess the implications of our findings on the use and application of key information technologies.

The ability to estimate the likelihood of future events based on current and historical data is essential to the decision making process of many government agencies. Successful predictions related to terror events and characterizing the risks will support development of options for countering these events. The predictive tasks involve both technical and social component models. The social components have presented a particularly difficult challenge. This paper outlines some technical considerations of this modeling activity. Both data and predictions associated with the technical and social models will likely be known with differing certainties or accuracies – a critical challenge is linking across these model domains while respecting this fundamental difference in certainty level. This paper will describe the technical approach being taken to develop the social model and identification of the significant interfaces between the technical and social modeling in the context of analysis of diversion of nuclear material.

Visual graph representations are increasingly used to represent, display, and explore scenarios and the structure of organizations. The graph representations of scenarios are readily understood, and commercial software is available to create and manage these representations. The purpose of the research presented in this paper is to explore whether these graph representations support quantitative assessments of the underlying scenarios. The underlying structure of the scenarios is the information that is being targeted in the experiment and the extent to which the scenarios are similar in content. An experiment was designed that incorporated both the contents of the scenarios and analysts’ graph representations of the scenarios. The scenarios’ content was represented graphically by analysts, and both the structure and the semantics of the graph representation were attempted to be used to understand the content. The structure information was not found to be discriminating for the content of the scenarios in this experiment; but, the semantic information was discriminating.

It is becoming increasingly difficult for biomedical research workers to get the wild primates they consider essential for their work. Successful primate ranching could help solve the problem. In 1967 a well-known animal dealer in Colombia, Mike Tsalickis of Leticia, released over 5000 squirrel monkeys on an island in the Amazon in the hope of quick breeding results. Five years later he estimated the island monkey population at over 20,000, and the experiment appeared to have been very successful; later counts, however, suggested considerable errors in the figures and that the monkeys had in fact decreased catastrophically. The authors describe this and other experiments, some successful, but only as a result of expensive supplemental feeding.