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Articles

Early Detection of Terrorism Outbreaks Using Prospective Space–Time Scan Statistics

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Pages 676-691 | Received 01 Jul 2011, Accepted 01 Mar 2012, Published online: 18 Oct 2012
 

Abstract

Terrorism is a complex phenomenon with high uncertainty involving a myriad of dynamic known and unknown factors. It is and will remain a challenge to predict or detect terrorism outbreaks at an early stage. This research presents an alternative approach for modeling terrorism activity, one that monitors and detects space–time clusters of terrorist incidents using prospective space–time scan statistics. Such clusters provide indicators of potential outbreaks of terrorist incidents. To evaluate the effectiveness of the approach, we analyze the terrorist incidents in the Consortium for the Study of Terrorism and Responses to Terrorism's (START) Global Terrorism Database (GTD) from 1998 to 2004. Clusters of terrorist events are detected at each time stamp and life trajectories of these clusters are constructed based on their space–time relationship to each other. Through the life trajectories and trends of clusters, we demonstrate how space–time scan statistics detect terrorism outbreaks at an early stage.

恐怖主义是个具有高度不确定性的复杂现象, 包含各种已知与未知的因素。在初始阶段预测或侦查恐怖主义的产生, 对当下与未来而言皆为重大的挑战。本研究展示模式化恐怖主义活动的另类方法, 透过前瞻性时空扫描统计, 监控与侦测恐怖主义活动的时空集群。这些集群对可能爆发的恐怖攻击事件提供了指标。为了衡量此一方法的有效性, 我们分析了1998至2004年间恐怖主义及对策研究集团 (START) 的全球反恐数据库 (GTD) 中的恐怖主义事件。恐怖主义事件的集群在每个时间戳中受到侦测, 并根据它们之间的时空关系建构其生命轨迹。透过生命轨迹与集群的趋势, 我们显示时空扫描统计如何在初始阶段侦测恐怖主义的发生。

El terrorismo es un fenómeno complejo con alto grado de incertidumbre que involucra una miríada de factores dinámicos conocidos y desconocidos. Es y seguirá siendo un reto predecir o detectar brotes de terrorismo con anticipación suficiente. En esta investigación se presenta un enfoque alternativo para modelar la actividad terrorista, enfoque que monitorea y detecta agrupaciones espacio–temporales de incidentes terroristas mediante el uso de estadísticas prospectivas de escaneo espacio–temporal. Tales agrupamientos nos proporcionan indicadores de potenciales brotes de incidentes terroristas. Para evaluar la efectividad de este enfoque, analizamos los incidentes terroristas registrados entre 1998 y 2004 en la Base de Datos del Terrorismo Global (BDTG) del Consorcio para el Estudio del Terrorismo y las Respuestas al Terrorismo (CERTRT). Los agrupamientos de eventos terroristas son detectados en cada registro temporal y las trayectorias de vida de estos agrupamientos se construyen con base en sus mutuas relaciones espacio–temporales. A través de las trayectorias de vida y tendencias de esos agrupamientos, demostramos cómo las estadísticas de exploración espacio–tiempo pueden detectar brotes de terrorismo en una etapa temprana.

Notes

This research was partially supported by the U.S. Department of Homeland Security through the National Consortium for the Study of Terrorism and Responses to Terrorism (START), grant number N00140510629. Diansheng Guo would like to acknowledge support by the National Science Foundation under Grant No. 0748813. Any opinions, findings, and conclusions or recommendations in this article are those of the authors and do not necessarily reflect the views of the U.S. Department of Homeland Security or the National Science Foundation. The authors would also like to thank Mary Thompson for her comments on the article.

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