Overview
- Examines and explains every aspect of an important ongoing research program in terrorism informatics
- Interdisciplinary perspective looks at three dimensions: methodological issues, database and computational techniques, and legal, social and privacy challenges
- Hsinchun Chen is a worldwide leader in data mining research and a prolific Springer author?
Part of the book series: Integrated Series in Information Systems (ISIS, volume 30)
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Table of contents (22 chapters)
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Research Framework: Overview and Introduction
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Dark Web Research: Computational Approach and Techniques
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Dark Web Research: Case Studies
Keywords
About this book
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.
Reviews
From the reviews:
“Chen’s 450-page monograph is a very detailed (yet understandable), up-to-date account of research into one very specific area of Web research. … the book can be interesting reading for academicians, researchers, and students at universities … . It is also recommended for researchers in security-related disciplines. … the book should also interest security specialists in the industry, especially those dealing with IT-related issues … . Overall, the book presents a wealth of research results on an important subject, in a consistent way.” (P. Navrat, ACM Computing Reviews, October, 2012)
Authors and Affiliations
Bibliographic Information
Book Title: Dark Web
Book Subtitle: Exploring and Data Mining the Dark Side of the Web
Authors: Hsinchun Chen
Series Title: Integrated Series in Information Systems
DOI: https://doi.org/10.1007/978-1-4614-1557-2
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Hardcover ISBN: 978-1-4614-1556-5Published: 16 December 2011
Softcover ISBN: 978-1-4899-9286-4Published: 03 March 2014
eBook ISBN: 978-1-4614-1557-2Published: 17 December 2011
Series ISSN: 1571-0270
Series E-ISSN: 2197-7968
Edition Number: 1
Number of Pages: XXVI, 454
Topics: Data Mining and Knowledge Discovery, IT in Business, Operations Research/Decision Theory