文章基本信息

标题：Big Data: An Approach for Detecting Terrorist Activities with People's Profiling
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作者：Oludare Isaac Abiodun ; Aman Jantan ; Abiodun Esther Omolara 等
期刊名称：Lecture Notes in Engineering and Computer Science
印刷版ISSN：2078-0958
电子版ISSN：2078-0966
出版年度：2018
卷号：2233&2234
页码：196-201
出版社：Newswood and International Association of Engineers
摘要：This research provides an empirical model approach to detecting terrorist. The modeling method is an empirical formula for measuring individual actor’s level of involvement in terrorism crime. Terrorists are gaining ground virtually in the most nation of the world. This has become a global challenge as the attacks have recorded millions of deaths of innocent people, incapacitated people, and destroyed properties. In addition, the attacks rendered most communities and countries economically dormant and create a complex crisis among the people. In the research approach, the mathematical model developed is used to detect person’s involvement in terrorism. Furthermore, the mathematical model result can be used to predict or calculate the outcome of the dependent parameter from the varying independents. In conclusion, the research objectives were achieved as there was a record of 0.26495 or 26.495% prediction on the overall test which determined the levels of optimization and improvement. Thus, we recommend that people’s profiling analysis has a significant contribution to terrorist detecting if integrated into the system as a solution to terrorist attacks.
关键词：Big data; Integration; Security; Optimization; Terrorist;