Dark Web : Exploring and Data Mining the Dark Side of the Web / by Hsinchun Chen.

Format:

Book

Author/Creator:

Chen, Hsinchun, author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Integrated series in information systems 1571-0270 ; 30.

Integrated Series in Information Systems, 1571-0270 ; 30

Language:

English

Subjects (All):

Data mining.

Information technology.

Business--Data processing.

Business.

Operations research.

Decision making.

Data Mining and Knowledge Discovery.

IT in Business.

Operations Research/Decision Theory.

Local Subjects:

Data Mining and Knowledge Discovery.

IT in Business.

Operations Research/Decision Theory.

Physical Description:

1 online resource (XXVI, 454 pages).

Edition:

First edition 2012.

Contained In:

Springer eBooks

Place of Publication:

New York, NY : Springer New York : Imprint: Springer, 2012.

System Details:

text file PDF

Summary:

The University of Arizona Artificial Intelligence Lab (AI Lab) Dark Web project is a long-term scientific research program that aims to study and understand the international terrorism (Jihadist) phenomena via a computational, data-centric approach. We aim to collect "ALL" web content generated by international terrorist groups, including web sites, forums, chat rooms, blogs, social networking sites, videos, virtual world, et cetera We have developed various multilingual data mining, text mining, and web mining techniques to perform link analysis, content analysis, web metrics (technical sophistication) analysis, sentiment analysis, authorship analysis, and video analysis in our research. The approaches and methods developed in this project contribute to advancing the field of Intelligence and Security Informatics (ISI). Such advances will help related stakeholders to perform terrorism research and facilitate international security and peace. This monograph aims to provide an overview of the Dark Web landscape, suggest a systematic, computational approach to understanding the problems, and illustrate with selected techniques, methods, and case studies developed by the University of Arizona AI Lab Dark Web team members. This work aims to provide an interdisciplinary and understandable monograph about Dark Web research along three dimensions: methodological issues in Dark Web research; database and computational techniques to support information collection and data mining; and legal, social, privacy, and data confidentiality challenges and approaches. It will bring useful knowledge to scientists, security professionals, counterterrorism experts, and policy makers. The monograph can also serve as a reference material or textbook in graduate level courses related to information security, information policy, information assurance, information systems, terrorism, and public policy.

Contents:

Chapter 1. Dark Web Research Overview

Chapter 2. Intelligence and Security Informatics (ISI): Research Framework

Chapter 3. Terrorism Informatics

Chapter 4. Forum Spidering

Chapter 5. Link and Content Analysis

Chapter 6. Dark Network Analysis

Chapter 7. Interactional Coherence Analysis

Chapter 8. Dark Web Attribute System

Chapter 9. Authorship Analysis

Chapter 10. Sentiment Analysis

Chapter 11. Affect Analysis

Chapter 12. Cybergate Visualization

Chapter 13. Dark Web Forum Portal

Chapter 14. Jihadi Video Analysis

Chapter 15. Extremist Youtube Videos

Chapter 16. Improvised Explosive Devices (IED) on Dark Web

Chapter 17. Weapons of Mass Destruction (WMD) on Dark Web

Chapter 18. Bioterrorism Knowledge Mapping

Chapter 19. Women's Forums on the Dark Web

Chapter 20. U.S. Domestic Extremist Groups

Chapter 21. International Falun Gong Movement on the Web

Chapter 22. Botnets and Cyber Criminals.

Other Format:

Printed edition:

ISBN:

978-1-4614-1557-2

9781461415572

Access Restriction:

Restricted for use by site license.