By Hsinchun Chen
The collage of Arizona synthetic Intelligence Lab (AI Lab) darkish net undertaking is a long term clinical study software that goals to review and comprehend the foreign terrorism (Jihadist) phenomena through a computational, data-centric procedure. We goal to assemble "ALL" websites generated by means of foreign terrorist teams, together with sites, boards, chat rooms, blogs, social networking websites, video clips, digital global, and so forth. we have now built numerous multilingual information 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 techniques and techniques constructed during this undertaking give a contribution to advancing the sphere of Intelligence and protection Informatics (ISI). Such advances may help comparable stakeholders to accomplish terrorism examine and facilitate foreign safeguard 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 recommendations, equipment, and case experiences constructed by way of the college of Arizona AI Lab darkish net group participants. This paintings goals to supply an interdisciplinary and comprehensible monograph approximately darkish internet examine alongside 3 dimensions: methodological concerns in darkish internet study; database and computational suggestions to help details assortment and information mining; and felony, social, privateness, and knowledge confidentiality demanding situations and ways. it's going to deliver beneficial wisdom to scientists, protection pros, counterterrorism specialists, and coverage makers. The monograph may also function a reference fabric or textbook in graduate point classes regarding info protection, info coverage, details insurance, info structures, terrorism, and public policy.
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Additional resources for Dark Web: Exploring and Data Mining the Dark Side of the Web
Identity theft, money laundering, arson and bombing, organized and violent activities, and cyber-terrorism) and causes great damage. We believe that KDD techniques can play a central role in improving counterterrorism and crime-fighting capabilities of intelligence, security, and law enforcement agencies by reducing the cognitive and information overload. Knowledge discovery refers to nontrivial extraction of implicit, previously unknown, and potentially useful knowledge from data. , predicting consumer behaviors, detecting credit card 26 2 Intelligence and Security Informatics (ISI): Research Framework Crime Data Mining Techniques Analysis Capability Criminal Network Analysis Spatial & Temporal Pettern Mining Text Mining Classification & Clustering Association Info Sharing & Collaboration Traffic Violation Sex Offense Theft Fraud Arson Organized Crime Violent Crime Cyber Crime Crime Types Public Harm Fig.
Qin, “On the Topology of the Dark Web of Terrorist Groups,” in Proceedings of the Intelligence and Security Informatics: IEEE International Conference on Intelligence and Security Informatics (ISI 2006), San Diego, CA, USA, May 2006. 2005 • Y. Zhou, J. Qin, G. Lai, E. Reid and H. Chen, “Building Knowledge Management System for Researching Terrorist Groups on the Web,” Proceedings of the AIS Americas Conference on Information Systems (AMCIS 2005), Omaha, NE, USA, August 2005. • E. Reid and H. Chen.
Zhou, J. Qin, G. Lai, E. Reid and H. Chen, “Building Knowledge Management System for Researching Terrorist Groups on the Web,” Proceedings of the AIS Americas Conference on Information Systems (AMCIS 2005), Omaha, NE, USA, August 2005. • E. Reid and H. Chen. “Mapping the Contemporary Terrorism Research Domain: Researchers, Publications, and Institutions Analysis,” ISI Conference 2005, Atlanta, GA, May 2005. • H. Chen, “Applying Authorship Analysis to Arabic Web Content,” ISI Conference 2005, Atlanta, GA, May 2005.