云计算智能数据驱动模型:连接点以打击全球恐怖主义

G. Goteng, Xueyu Tao
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引用次数: 2

摘要

基于2005年至2015年全球恐怖主义数据库(GTD)的数据,我们使用有向图的方法得出了一个相互关联的恐怖主义活动网络。我们开发了一个名为CloudTerrorAlert (CTA)的分析模型,并在一个基于云的环境中实施,该环境分析GTD数据,以帮助全球反恐安全机构进行协作和决策。我们的CTA算法比较了三组用于预测的数据-通信(电子邮件和电话),交易(汇款和武器购买)和运输(跨越边界和国家的运动),使用建议的概率阈值至少为0.3来决定是否即将发生恐怖袭击。该模型的原型将恐怖分子活动的分布式数据连接起来,证明该系统可以对使用基于云的技术打击全球恐怖主义产生非常重大的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloud Computing Intelligent Data-Driven Model: Connecting the Dots to Combat Global Terrorism
We used directed graph to come up with an interconnected network of terrorists' activities based on data obtained from the Global Terrorism Database (GTD) from 2005 to 2015. We developed an analytical model called CloudTerrorAlert (CTA) and implemented it within a cloud-based environment that analyzes GTD data to aid collaboration and decision making by counter-terrorist security agents around the world. Our CTA algorithm compares three sets of data for prediction - communication (emails and phone calls), transaction (money transfers and arms purchases), and transportation (movements across boundaries and countries) using a proposed probability threshold that is at least 0.3 to make a decision on whether or not a terror attack is about to occur. A prototype of the model which connects the distributed data on terrorists' activities as implemented proved that the system could have very significant impact on using cloud-based technologies in the fight against global terrorism.
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