# Intuitive Visualization Of The Intelligence For The Run-Down Of Terrorist Wire-Pullers

Yoshiharu Maeno∗**and Yukio Ohsawa**†
October 25, 2018

## Abstract

The investigation of the terrorist attack is a time-critical task. The investigators have a limited time window to diagnose the organizational background of the terrorists, to run down and arrest the wire-pullers, and to take an action to prevent or eradicate the terrorist attack. The intuitive interface to visualize the intelligence data set **stimulates the investigators' experience and knowledge, and aids them in decision-making**
for an immediately effective action. This paper presents a computational method to analyze the intelligence data set on the collective actions of the perpetrators of the attack, and to visualize it into the form of a social network diagram which predicts the positions where the **wire-pullers**
conceals themselves.

## 1 Introduction

Terrorist attacks cause great economic, social and environmental impacts. The disaster by the terrorist attacks is different from the emergence **arising from**
earthquakes or hurricanes, in that active non-routine responses are always necessary, and often possible. The investigation of the terrorist attacks and the responses are, however, a time-critical task. The investigators **have a limited** time window to diagnose the organizational background of the terrorists, to run down and arrest the wire-pullers, and to take an action to prevent **or eradicate** the attack. The arrest of the wire-pullers is more likely to dismantle the terrorist organization than that of the perpetrators. This is because a limited number of persons can provide the perpetrators with financial supports **and elaborate** plots, while a perpetrator can be replaced by another person easily.

Let us show an example in the 9/11 terrorist attack in 2001. Mustafa A.

Al-Hisawi, whose alternate name was Mustafa Al-Hawsawi, was alleged **to be**
∗**Corresponding author, Graduate School of Systems Management, Tsukuba University,**
Otsuka Bunkyo-ku, 112-0012 Tokyo, Japan. email: maeno.yoshiharu@nifty.com.

†**School of Engineering, University of Tokyo, Hongo Bunkyo-ku, 113-8656 Tokyo, Japan.**
email: ohsawa@sys.t.u-tokyo.ac.jp.