Analyzing behavior signatures for terrorist attack forecasting. (April 2013)

• Record Type: Journal Article
• Authors: Reed, Gregory S; Colley, Wesley N; Aviles, Steven M
• Other Names: Henshaw Michael guest-editor.; Brathen Karsten guest-editor.; Isler Veysi guest-editor.
• Is Part Of: Journal of defense modeling and simulation. Volume 10:Number 2(2013)
• Page Start: 203
• Page End: 213
• Publication Date: 2013-04
• Subjects: behavior signatures -- data mining -- statistical methods -- text mining; Military art and science -- Computer simulation -- Periodicals; 355.0011305
• DOI: 10.1177/1548512911421184
• Languages: English
• ISSNs: 1548-5129

Abstract

In this paper we outline statistical methods used to analyze the behavior signatures that are hidden deep within data on terrorist attacks. These methods have the potential to allow military commanders to identify trends in attacks and to make informed decisions about how best to prevent future attacks. While this work focuses primarily on terrorist attacks that have occurred during Operation Iraqi Freedom, the methodology can be expanded and applied to a variety of areas. With the terrorists' advantage of the element of surprise, analyzing their behavior may appear to be a very daunting task; however, it is demonstrated that even a collection of largely random data can often lead to insightful inferences. This paper provides a discussion of the project as a whole, the challenges faced in data collection and analysis, the methodology used, and the results and implications of the study.