An agent-based model and computational framework for counter-terrorism and public safety based on swarm intelligencea

Andrew J Park,Herbert H Tsang,Mengting Sun,Uwe Glässer

doi:10.1186/2190-8532-1-23

Abstract

Public safety has been a great concern in recent years as terrorism occurs everywhere. When a public event is held in an urban environment like Olympic games or soccer games, it is important to keep the public safe and at the same time, to have a specific plan to control and rescue the public in the case of a terrorist attack. In order to better position public safety in communities against potential threats, it is of utmost importance to identify existing gaps, define priorities and focus on developing approaches to address those. In this paper, we present a system which aims at providing a decision support, threats response planning and risk assessment. Threats can be in the form of Chemical, Biological, Radiological, Nuclear and Explosive (CBRNE) weapons and technologies. In order to assess and manage possible risks of such attacks, we have developed a computational framework of simulating terrorist attacks, crowd behaviors, and police or safety guards’ rescue missions. The characteristics of crowd behaviors are modeled based on social science research findings and our own virtual environment experiments with real human participants. Based on gender and age, a person has a different behavioral characteristic. Our framework is based on swarm intelligence and agent-based modeling, which allows us to create a large number of people with specific behavioral characteristics. Different test scenarios can be created by importing or creating 3D urban environments and putting certain terrorist attacks (such as bombs or toxic gas) on specific locations and time-lines.

Highlights

Since September 11, 2001, counter-terrorism and national security have become the main focus of defense and security authorities around the globe
In [3], we discussed the potential of enhancing the framework to be used in the analysis of terrorism and counter-terrorism. This paper introduces such an enhanced framework that builds on top of our previous research (Mastermind) and makes an extension to allow the simulation of larger number of agents
Events We have modeled a real-time situation analysis in GENIUS, which is a part of the Event Generation Module (EGM)

Summary

Introduction

Since September 11, 2001, counter-terrorism and national security have become the main focus of defense and security authorities around the globe. Governments and security agencies have been actively trying to improve their capabilities by funding and supporting innovative science and technology approaches that address national public safety and security needs and provide tools for CBRNE response and preparedness. In order to better position communities against potential threats, it is of utmost importance to identify existing gaps, define priorities and focus on developing approaches to address those. In Canada, national security agencies have identified different priority areas to improve CBRNE response capabilities and to organize counter-terrorism activities. One major area is Risk Assessment and Priority Setting; i.e. to develop advanced tools and techniques that allow for a reliable understanding of threats, consolidated risk assessment, and rating of threat scenarios. A well-defined risk assessment approach leads to a systematic analysis of capability gaps and provides guidelines for setting of investment priorities in order to address the most critical gaps [1]

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