By Hsinchun Chen
The collage of Arizona synthetic Intelligence Lab (AI Lab) darkish net undertaking is a long term clinical examine application that goals to review and comprehend the overseas terrorism (Jihadist) phenomena through a computational, data-centric method. We target to assemble "ALL" websites generated by way of overseas terrorist teams, together with sites, boards, chat rooms, blogs, social networking websites, video clips, digital international, and so forth. now we have built a variety of multilingual info mining, textual content mining, and net mining recommendations to accomplish hyperlink research, content material research, net metrics (technical sophistication) research, sentiment research, authorship research, and video research in our study. The ways and techniques constructed during this venture give a contribution to advancing the sphere of Intelligence and safety Informatics (ISI). Such advances may help comparable stakeholders to accomplish terrorism learn and facilitate foreign protection and peace.
This monograph goals to supply an summary of the darkish net panorama, recommend a scientific, computational method of realizing the issues, and illustrate with chosen ideas, tools, and case reviews built by means of the collage of Arizona AI Lab darkish net staff contributors. This paintings goals to supply an interdisciplinary and comprehensible monograph approximately darkish net learn alongside 3 dimensions: methodological concerns in darkish internet examine; database and computational options to help details assortment and knowledge mining; and criminal, social, privateness, and information confidentiality demanding situations and ways. it's going to deliver helpful wisdom to scientists, safety execs, counterterrorism specialists, and coverage makers. The monograph may also function a reference fabric or textbook in graduate point classes regarding info safeguard, info coverage, details coverage, details structures, terrorism, and public policy.
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Additional info for Dark Web: Exploring and Data Mining the Dark Side of the Web
14 1 Dark Web Research Overview 2009 • Y. Zhang, Y. Dang, and H. Chen, “Gender Difference Analysis of Political Web Forums: An Experiment on an International Islamic Women’s Forum,” in Proceedings of the IEEE International Intelligence and Security Informatics Conference, Dallas, TX, June 2009. • Y. Zhang, S. Zeng, L. Fan, Y. Dang, C. Larson, and H. Chen, “Dark Web Forums Portal: Searching and Analyzing Jihadist Forums,” in Proceedings of the IEEE International Intelligence and Security Informatics Conference, Dallas, TX, June 2009.
2005 • H. Chen and F. Wang, “Artificial Intelligence for Homeland Security,” IEEE Intelligent Systems, Special Issue on Artificial Intelligence for National and Homeland Security, Pages 12–16, September/October 2005. • H. Chen, “Applying Authorship Analysis to Extremist-Group Web Forum Messages,” IEEE Intelligent Systems, Special Issue on Artificial Intelligence for National and Homeland Security, Pages 67–75, September/October 2005. • Y. Zhou, E. Reid, J. Qin, G. Lai, and H. S. Domestic Extremist Groups on the Web: Link and Content Analysis,” IEEE Intelligent Systems, Special Issue on Artificial Intelligence for National and Homeland Security, Pages 44–51, September/October 2005.
Huang, and H. Chen, “Identification of Extremist Videos in Online Video Sharing Sites,” in Proceedings of the IEEE International Intelligence and Security Informatics Conference, Dallas, TX, June 2009. 2008 • H. Chen and the Dark Web Team, “IEDs in the Dark Web: Genre Classification of Improvised Explosive Device Web Pages,” in Proceedings of the IEEE International Intelligence and Security Informatics Conference, Taipei, Taiwan, June 2008. Springer Lecture Notes in Computer Science. • H. Chen and the Dark Web Team, “Discovery of Improvised Explosive Device Content in the Dark Web,” in Proceedings of the IEEE International Intelligence and Security Informatics Conference Taipei, Taiwan, June 2008.