Predicting Terroristic Attacks in Urban Environments: An Internet- of-Things Approach

In the recent years we have witnessed a number of important terroristic incidents, in major cities all around the world (e.g., 911 in New York, 11-M in Madrid, 7/7 in London). These incidents have revealed the vulnerabilities of urban environments, against terroristic plans and have created significant pressure towards devising novel tools and techniques for timely predicting the intentions and plans of terrorists. In this paper, we introduce a blueprint Internet-of-Things architecture for predicting terroristic attacks. The architecture allows Law enforcement agencies to exploit multiple data sources, (including SIGINT, OSINT and HUMINT) towards acquiring information associated with terroristic action, while at the same time providing powerful reasoning capabilities towards transforming raw events into meaningful alerts. We also illustrate the implementation of a terroristic prediction system based on this architecture, along with its use in the scope of a validating scenario.