A Department of Homeland Security Center of Excellence led by the University of Maryland

Dissuading Adversaries and their Radiological/Nuclear Pathways: Integrating Deterrence Theory and Analytics in the Global Nuclear Detection Architecture (GNDA)


Dissuading Adversaries and their Radiological/Nuclear Pathways: Integrating Deterrence Theory and Analytics in the Global Nuclear Detection Architecture (GNDA)

Project Details

Abstract: 

This multidisciplinary project expands upon several extant analytical and computational models and data collections of potential radiological or nuclear (RN) adversary behaviors that START researchers have previously developed. This project will integrate these disparate risk assessment tools into a single, comprehensive model in order to allow analysis of the deterrent and deflective effects of a range of potential defensive investments in the Global Nuclear Detection Architecture (GNDA) on adversary behaviors in or affecting the domestic United States. The existing models variously assess: adversaries’ likely interest in, means of acquiring and weaponizing RN materials, and the success thereof; RN targeting preferences; RN weapon command and control preferences; and RN smuggling route preferences. These will be integrated with other forecasting models to expressly take into account the impact of future technological and geopolitical developments on adversary RN behavior. 

The project will use cutting-edge non-state actor deterrence theory and game-theoretical approaches to combine these previous models, which themselves integrate deep qualitative and contextual empirical data on violent non-state actors with theoretical insights drawn from terrorism studies, organizational psychology, political science, criminology, sociology, and engineering. The resulting model will instantiate detailed adversary profiles and GNDA capabilities in a highly granular geospatial network to explore the systemic and strategic influences on RN adversary behaviors. This will help GNDA analysts to incorporate the dynamic nature of the adversarial threat when developing and implementing policies and investments.

Timeframe

Project Period: 
October 2013 to September 2018