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논문검색

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

초록

영어

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.

목차

Abstract
 1. Introduction
 2. IoT-based System Architecture for Predicting Terroristic Attacks in Urban Environment
 3. Low-Level Information Collection and Processing
  3.1. Sensor Data Collection
  3.2. Sensor Data Processing
 4. Terroristic Events Database and Data Management Interfaces
  4.1. Database Modeling and Terroristic Indicators
  4.2. Data Management Applications
 5. Reasoning Layer
  5.1. Short-Term Reasoning
  5.2. Long-Term Reasoning
  5.3. Medium-Term Reasoning
  5.4. TRK Application
 6. Validating Scenario
  6.1. Overview
  6.2. Pre-Operational (Off-Line) Phase
  6.3. Real-Time Phase
 7. Conclusions
 8. Related Works
 Acknowledgements
 References

저자정보

  • Stavros Petris Athens Information Technology, 0,8km Markopoulo Ave., P.O. Box 68, GR-19002 Peania, Greece
  • Christos Georgoulis Athens Information Technology, 0,8km Markopoulo Ave., P.O. Box 68, GR-19002 Peania, Greece
  • John Soldatos Athens Information Technology, 0,8km Markopoulo Ave., P.O. Box 68, GR-19002 Peania, Greece
  • Ilaria Giordani Consorzio Milano Ricerche, Via Cozzi 53, 20125 Milano, Italy
  • Raul Sormani Consorzio Milano Ricerche, Via Cozzi 53, 20125 Milano, Italy
  • Divna Djordjevic Consorzio Milano Ricerche, Via Cozzi 53, 20125 Milano, Italy

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