Dismantling terrorist networks: Evaluating strategic options using agent-based modeling

Abstract Dismantling dark networks remains a critical goal for the peace and security of our society. Terrorist networks are the most prominent instantiation of dark networks, and they are alive and well. Attempts to preemptively disrupt these networks and their activities have met with both success and failure. In this paper, we examine the impacts of four common strategies for dismantling terrorist networks. The four strategies are: leader-focused, grassroots, geographic, and random. Each of these strategies has associated pros and cons, and each has different impacts on the structure and capabilities of a terrorist network. Employing a computational experimentation methodology, we simulate a terrorist network and test the effects of each strategy on the resiliency of that network. In addition, we test scenarios in which the terrorist network has (or does not have) information about an impending attack. Our work takes a structural perspective to the challenge of addressing terrorist networks. Specifically, we show how various strategies impact the structure of the network in terms of its resiliency and capacity to carry out future attacks. This paper also provides a valuable overview of how to use agent-based modeling for the study of complex problems in the terrorism, conflict studies, and security study domains.

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