Stochastic modeling of a terrorist event via the ASAM system
Stochastic modeling of a terrorist event via the ASAM system
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通过 ASAM 系统对恐怖事件进行随机建模
DOI：
10.1109/icsmc.2004.1401098
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
P. Willett
中科院分区：
文献类型：
--
作者：
Satnam Singh;J. Allanach;Haiying Tu;K. Pattipati;P. Willett
恐怖分子网络能够同时进行复杂的攻击（最近一次是 2004 年 3 月 11 日在西班牙马德里发生的攻击），这表明迫切需要开发用于反恐分析的信息技术工具。这些技术可以使情报分析人员能够更快地查找信息，跨机构共享和协作，更好地“连接点”，并进行更快更好的分析。康涅狄格大学正在开发其中一项技术，即自适应安全分析和监控（ASAM）系统。本文介绍了 ASAM 系统并讨论了其功能。使用特征辅助多目标跟踪、隐马尔可夫模型 (HMM) 和贝叶斯网络 (BN) 的组合对 2004 年雅典奥运会的漏洞进行建模并识别异常行为模式。 ASAM 系统的功能通过应用于 2004 年雅典奥运会上恐怖活动的两个假设模型来说明。
The ability of terrorist networks to conduct sophisticated and simultaneous attacks - the most recent one on March 11, 2004 in Madrid, Spain - suggests that there is a significant need for developing information technology tools for counter-terrorism analysis. These technologies could empower intelligence analysts to find information faster, share, and collaborate across agencies, "connect the dots" better, and conduct quicker and better analyses. One such technology, the adaptive safety analysis and monitoring (ASAM) system, is under development at the University of Connecticut. In this paper, the ASAM system is introduced and its capabilities are discussed. The vulnerabilities at the Athens 2004 Olympics are modeled and patterns of anomalous behavior are identified using a combination of feature-aided multiple target tracking, hidden Markov models (HMMs), and Bayesian networks (BNs). Functionality of the ASAM system is illustrated by way of application to two hypothetical models of terrorist activities at the Athens 2004 Olympics.