<p><p>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 generate
Dark Web: Exploring and Data Mining the Dark Side of the Web
β Scribed by Hsinchun Chen (auth.)
- Publisher
- Springer-Verlag New York
- Year
- 2012
- Tongue
- English
- Leaves
- 459
- Series
- Integrated Series in Information Systems 30
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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, etc. 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.
β¦ Table of Contents
Front Matter....Pages i-xxvi
Front Matter....Pages 1-1
Dark Web Research Overview....Pages 3-18
Intelligence and Security Informatics (ISI): Research Framework....Pages 19-30
Terrorism Informatics....Pages 31-41
Front Matter....Pages 43-43
Forum Spidering....Pages 45-69
Link and Content Analysis....Pages 71-90
Dark Network Analysis....Pages 91-103
Interactional Coherence Analysis....Pages 105-126
Dark Web Attribute System....Pages 127-151
Authorship Analysis....Pages 153-169
Sentiment Analysis....Pages 171-201
Affect Analysis....Pages 203-225
CyberGate Visualization....Pages 227-256
Dark Web Forum Portal....Pages 257-270
Front Matter....Pages 271-271
Jihadi Video Analysis....Pages 273-293
Extremist YouTube Videos....Pages 295-318
Improvised Explosive Devices (IED) on Dark Web....Pages 319-339
Weapons of Mass Destruction (WMD) on Dark Web....Pages 341-353
Bioterrorism Knowledge Mapping....Pages 355-367
Womenβs Forums on the Dark Web....Pages 369-389
US Domestic Extremist Groups....Pages 391-405
Front Matter....Pages 271-271
International Falun Gong Movement on the Web....Pages 407-425
Botnets and Cyber Criminals....Pages 427-439
Back Matter....Pages 441-451
β¦ Subjects
Data Mining and Knowledge Discovery; Business Information Systems; Operation Research/Decision Theory
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