Dark Web: Exploring and Data Mining the Dark Side of the Web

The internet and web have become indispensable in our information dissemination and retrieval practices, but the web is not just utilised for peaceful purposes – terrorists and extremists also use it to recruit new members, spread propaganda and plan attacks across the world. Funded by the National Science Foundation and other federal agencies, Hsinchun Chen and his Artificial Intelligence Laboratory at the University of Arizona have created the AI Lab Dark Web Project, which aims systematically to collect and analyse all terrorist‐generated content on the web. This includes websites, forums, chat rooms, blogs, social networking sites, videos, virtual worlds and so on.

Analysing web content has become increasingly important to the intelligence agencies and research communities that monitor these groups, yet the sheer amount of material to be analysed is so great that it can quickly overwhelm traditional methods of monitoring and surveillance. Search engines only explore what is known as the surface web. The invisible web, also known as the deep web, which includes these dark web fora, is estimated to contain 500 times as much information as the surface web. The goal of the Dark Web Project is to develop and use automated tools to systematically collect and analyse terrorist content from the internet.

The book reports on the ongoing research programme in terrorism informatics – the AI Lab Dark Web Project. It describes the dark web landscape of international terrorism, suggests a systematic, computational approach to understanding its problems, and presents techniques, methods and case studies developed by the AI Lab Dark Web team.

The book presents the subject in three parts. Part 1 provides an overview and introduction to the AI Lab Dark Web Project, the research framework and terrorism informatics. Part 2 describes in detail the computational techniques and analyses as applied in the execution of the project. Part 3 presents a number of case studies that the project focuses on, inter alia, Jihadi video analysis, extremist YouTube videos, weapons of mass destruction on the dark web, bio‐terrorism knowledge mapping, women's fora on the dark web, US domestic extremist groups and cyber criminals.

The focus of the work is very much on the methodology and computational techniques of the research developed to uncover terrorist activities on the dark web. Furthermore, attention is given to legal, social, privacy and data confidentiality challenges and approaches. The book provides useful and detailed information to those interested in terrorism as well those who conduct data and web mining. Interested persons would include scientists, researchers, students, security professionals, counterterrorism experts and policy makers. Reference lists at the end of each chapter provide readers with references to more material on the subject.

Those readers who are more interested only in learning about the web activities of terrorists may find reading through the research‐related detail somewhat tedious. But it remains a very interesting and, in certain respects, frightening work to read.