软件导刊2019，Vol.18Issue(1)：128-131,143,5.DOI:10.11907/rjdk.182658
基于特征画像的恐怖组织袭击偏好研究
Research on Attacking Preference of Terrorist Organization Based on Feature Profiling
摘要
Abstract
In order to effectively analyze multidimensional characteristic data of terrorist organizations and the interrelationship between the characteristic data, we select five typical international terrorist organizations from the Global Terrorism Database.Based on feature profiling, we use the method of statistics, machine learning, association rule mining and geographic information system to analyze the attacking characteristic attributes.According to the results, attacking preferences of the five typical terrorist organizations are considerably related to the attack regions but they all prefer to choose the weapons of explosives/bombs and firearms;in the association characteristic attributes, the associations of the three types of attributes, namely attack type, target type and weapon type are obviously correlated.The method is suitable for mining the characteristics of different potential terrorists in the intelligence analysis of counter-terrorism.关键词
恐怖组织/特征画像/全球恐怖主义数据库/关联规则挖掘/梯度提升决策树Key words
terrorist organization/feature profiling/the global terrorism database/association rule mining/gradient boosting decision tree分类
信息技术与安全科学引用本文复制引用
唐正,朱衍丞,邱凌峰,郑超慧..基于特征画像的恐怖组织袭击偏好研究[J].软件导刊,2019,18(1):128-131,143,5.基金项目
国家自然科学基金项目(71704183) （71704183）
