Data-driven Country Safety Monitoring Terrorist Attack Prediction

D. Spiliotopoulos, C. Vassilakis, Dionisis Margaris
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引用次数: 3

Abstract

Terrorism is a key risk for prospective visitors of tourist destinations. This work reports on the analysis of past terrorist attack data, focusing on tourist-related attacks and attack types in Mediterranean EU area and the development of algorithms to predict terrorist attack risk levels. Data on attacks in 10 countries have been analyzed to quantify the threat level of tourism-related terrorism based on the data from 2000 to 2017 and formulate predictions for subsequent periods. Results show that predictions on potential target types can be derived with adequate accuracy. Such results are useful for initiating, shifting and validating active terrorism surveillance based on predicted attack and target types per country from real past data.
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数据驱动的国家安全监测恐怖袭击预测
恐怖主义是旅游目的地潜在游客面临的主要风险。这项工作报告了对过去恐怖袭击数据的分析,重点关注地中海欧盟地区与游客有关的袭击和袭击类型,以及预测恐怖袭击风险水平的算法的发展。对10个国家的袭击数据进行了分析,以2000年至2017年的数据为基础,量化与旅游相关的恐怖主义威胁水平,并制定后续时期的预测。结果表明,对潜在目标类型的预测具有足够的准确性。这些结果有助于根据过去的真实数据,根据预测的攻击和每个国家的目标类型,启动、转移和验证主动恐怖主义监视。
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