TY - JOUR
T1 - Dismantling terrorist networks
T2 - Evaluating strategic options using agent-based modeling
AU - Keller, Jared P.
AU - Desouza, Kevin C.
AU - Lin, Yuan
N1 - Funding Information:
We would like to thank Marissa Lavelle for her diligent editing of previous drafts of the paper. All errors and omissions remain our responsibility. Jared P. Keller has a Masters in Information Management from the University of Washington. His primary research interests are in devising novel methods of information collection, composition, and incorporating artificial intelligence techniques to assign context and credibility to information. He is currently developing tools for data collection and analysis in the automotive, travel, and financial industries. million of research funding and is a fellow of the Royal Society of the Arts. Kevin C. Desouza is on the faculty of the Information School at the University of Washington. He holds adjunct appointments in the College of Engineering and Daniel J. Evans School of Public Affairs. His research interests are in the areas of strategic innovation, knowledge management, government and national security programs, and security studies. He has published over 100 papers, seven books, and has briefed over 50 government and private organizations. He has received over is on the faculty of the Information School at the University of Washington. He holds adjunct appointments in the College of Engineering and Daniel J. Evans School of Public Affairs. His research interests are in the areas of strategic innovation, knowledge management, government and national security programs, and security studies. He has published over 100 papers, seven books, and has briefed over 50 government and private organizations. He has received over $1.2.2 Yuan Lin is a doctoral candidate in the Information School, University of Washington. Her research interests involve individual knowledge transfer, organizational social networks, and social network simulation. She's now investigating the impact of social networks on intra-organizational knowledge transfer (especially for tacit knowledge). Prior to pursuing a doctorate, she received her BA in Information Management and Technology from Beijing University and her MA in Management Science and Engineering from Tsinghua University in China.
PY - 2010/9
Y1 - 2010/9
N2 - 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.
AB - 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.
KW - Agent-based modeling
KW - Counter-terrorism strategies
KW - Dark networks
KW - Network resiliency
KW - Terrorism
KW - Terrorist networks
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U2 - 10.1016/j.techfore.2010.02.007
DO - 10.1016/j.techfore.2010.02.007
M3 - Article
AN - SCOPUS:77955057636
SN - 0040-1625
VL - 77
SP - 1014
EP - 1036
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
IS - 7
ER -