Uncovering and Penetrating CBRN Networks: A General Methodology for Mapping Covert Social Networks
Abstract
This project seeks to develop a basic science methodology for identifying and penetrating terrorist networks preparing Chemical, Biological, Radiological, or Nuclear (CBRN) attacks against the United States or her allies. It is widely acknowledged that a successful CBRN attack requires a considerable degree of technical skill in addition to the materials themselves. In other words, assembling a complex CBRN device without knowledge of how to handle the necessary materials is unusually likely to result in lethal, wasteful, and relatively public accidents that terrorist groups cannot tolerate. The needed skills include both formal scientific or engineering schooling as well as “tacit knowledge” that can only be obtained from hands-on training and experience. Using recent developments in network theory, in particular the Affiliational Ecology Model (AEM) in Blau space, we seek to develop a general theoretical framework for identifying scientists who are at risk for recruitment into terrorist networks and possess the tacit knowledge necessary for a successful CBRN attack. Our approach offers numerous advantages over existing methods. First, the AEM produces a dynamic model of competition among organizations in a demographic space (i.e., “Blau space”). This allows us to identify current and future hotspots of recruiting into adversarial organizations without defaulting to crude profiling methods. It is not a person’s characteristics that matter, but rather their proximity to terrorist groups in an evolving ecological space. Second, the careers of highly educated scientific experts who are necessary to producing effective CBRN devices are largely public, whereas dangerous radiological, biological, or chemical agents are relatively easy to conceal. We thus orient our method to make maximum use of data that are inexpensive and simple to obtain, while still focusing on a critical component of CBRN device production. Third, the AEM provides basic principles that are useful for uncovering terrorist networks when only partial information is available. Having identified key personnel who may be, or have been, recruited into terrorist organizations we hope to trace their networks so as to uncover virtually the entire terrorist group. While this work is especially relevant to countering CBRN terrorism, the resulting methodology will be generally applicable to a variety of covert social networks such as religious cults, criminal cartels, and human trafficking rings. Its effectiveness is expected to be highest when it is able to focus on individuals with relatively uncommon expertise (e.g., nuclear scientists). Perhaps most important, we believe this work has significant potential to improve the accuracy of identification of persons of interest while reducing the “harassment rate”, or the tendency for innocent people to become the focus of official attention.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 26, 2016
- Source ID
- HDTRA11510065
Entities
People
- Matthew E Brashears
Organizations
- Defense Threat Reduction Agency
- University of South Carolina