Terror net

A team of computational scientists are using new approaches to track the moves of terrorists and extremists online.


Funded by the National Science Foundation and other federal agencies, Hsinchun Chen and his Artificial Intelligence Lab at the University of Arizona have created the Dark Web project, which aims to systematically collect and analyse all terrorist-generated content on the web.


Because of its vital role in coordinating terror activities, 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.


This is where the Dark Web project comes in. Using advanced techniques such as web spidering, link analysis, content analysis, authorship analysis, sentiment analysis and multimedia analysis, Chen and his team can find, catalogue and analyse extremist activities online.


According to Chen, scenarios involving vast amounts of information and data points are ideal challenges for computational scientists, who use the power of advanced computers and applications to find patterns and connections where humans can not.


One of the tools developed by Dark Web is a technique called Writeprint, which automatically extracts thousands of multilingual, structural, and semantic features to determine who is creating ‘anonymous’ content online.


Writeprint can look at a posting on an online bulletin board, for example, and compare it with writings found elsewhere on the internet. By analysing these certain features, it can determine with more than 95 percent accuracy if the author has produced other content in the past. The system can then alert analysts when the same author produces new content, as well as where on the internet the content is being copied, linked to or discussed.


Dark Web also uses complex tracking software called web spiders to search discussion threads and other content to find the corners of the internet where terrorist activities are taking place.


Although Dark Web’s capabilities are being used to study the online presence of extremist groups and other social movement organisations, Chen sees applications for the web mining approach in other academic fields.


‘What we are doing is using this to study societal change,’ Chen said. ‘Evidence of this change is appearing online, and computational science can help other disciplines better understand this change.’