Terrorist Activity Evaluation and Pattern Detection (TAE&PD) in Afghanistan: A Knowledge Discovery and Data Mining (KDDM) Approach for Counter-Terrorism

Abstract

Data mining (DM) is primarily used by businesses to discover customer tendencies to guarantee future profit opportunities. In the TAE&PD project we intend to incorporate a KDDM methodology using open source applications to gather, preprocess, model, evaluate and identify patterns of terrorism activity that may prove useful to counter-terrorism and strengthen homeland security in Afghanistan. We will experiment using real terrorism incidents data from the Worldwide Incidents Tracking System (WITS) of the National Counterterrorism Center (NCTC). The project seeks to discover terrorism trends based on specific incident factors, help in the evaluation of war in Afghanistan and demonstrate a KDDM approach that could be applied (proof of concept) to national security. Project results may uncover valuable information regarding terrorist hot spots to determine geographical mobilization of security forces resources in the region.

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Document Details

Document Type
Technical Report
Publication Date
Aug 28, 2012
Accession Number
ADA581564

Entities

People

  • Alfredo Cruz
  • Jeff Duffany
  • Jose Pou

Organizations

  • Polytechnic University of Puerto Rico

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Afghanistan
  • Counterterrorism
  • Data Analysis
  • Data Mining
  • Detection
  • Homeland Security
  • Information Science
  • Language
  • Machine Learning
  • National Security
  • Security
  • Statistics
  • Terrorism
  • Terrorists
  • Test And Evaluation
  • Visualizations

Readers

  • Distributed Systems and Data Platform Development
  • Political Violence and Terrorism Studies.
  • Systems Analysis and Design

Technology Areas

  • AI & ML