Cloud Computing Intelligent Data-Driven Model: Connecting the Dots to Combat Global Terrorism

Abstract

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.