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ISIS and other international terrorist organizations rely on the Internet to disseminate their extremist rhetoric and to recruit people to their cause, particularly through popular online social media applications. Any meaningful counterterrorism strategy must, therefore, account for the ways in which terrorist organizations use the Internet to prey on young, manipulable minds who are drawn to radical ideas and propaganda and to the desire to serve a cause larger than themselves. This article outlines the ways in which extremist organizations use the Internet to ensnare new recruits, analyzes the implications of cyber-recruitment on existing counterterrorism techniques, and suggests ways in which the U.S. government can work with Internet service providers and other major cyber corporations to better address this growing threat.

This report contains findings from the Advanced Research Workshop supported by the NATO Science for Peace and Security Programme on terrorists’ use of the Internet, held at Dublin City University on 27th-29th June 2016. The event was co-organised by the Cyberterrorism Project and the VOX-POL Network of Excellence. The workshop consisted of a total of 31 presentations, followed by a roundtable discussion during which participants formulated a set of recommendations. 60 delegates attended the symposium, from 13 different countries, including researchers and representatives from NATO HQ, NATO CCD-COE, UNICRI, the European Defence Agency, the Bavarian Police Academy and the Italian Carabinieri. This report provides summaries of each of the presentations and presents the workshop’s final recommendations.

Reacting to a series of terrorist attacks, the European Union has tasked Europol to establish an Internet Referral Unit (EU IRU) to counter terrorist propaganda. The political statement entailed a clear commitment to fundamental rights including data protection. This paper analyses the present and future applicable legal bases and elaborates on challenges connected to the practical implementation of the EU IRU. It also explains why Europol is often referred to as “the most controlled police
agency in the world”. The paper concludes that it is possible to tackle terrorism propaganda online in a
data protection compliant manner

What characterises social media radicals? And why some people become attracted to radicalisation? To explore answers to these questions, a number of tweets posted by a group of suspected radicals tweeting in Arabic were analysed using social network analysis and machine learning. The study revealed that these suspected radicals’ networks showed significant interaction with others; but this interactivity is only significant quantitatively as the interaction is not reciprocated. With regards to why these suspected radicals became attracted to radicalisation, Topic Modelling revealed these suspected radicals’ tweets underpinned a perceived injustice that they believed the Secret Police and the Government inflicted upon them. Overall, the study has shown that data science tools have the potential to inform our understanding of online radicalisation. It is hoped this exploratory study will be the basis for a future study in which the research questions will be answered using a larger sample.

Since the inception of the World Wide Web, security agencies, researchers, and analysts have focused much of their attention on the sentiment found on hate-inspired web-forums. Here, one of their goals has been to detect and measure users’ affects that are expressed in the forums as well as identify how users’ affects change over time. Manual inspection has been one way to do this; however, as the number of discussion posts and sub-forums increase, there has been a growing need for an automated system that can assist humans in their analysis. The aim of this paper, then, is to detect and measure a number of affects expressed in written text on Stormfront.org, the most visited hate forum on the Web. To do this, we used a machine learning approach where we trained a model to recognize affects on three sub-forums: Ideology and Philosophy, For Stormfront Ladies Only, and Stormfront Ireland. The training data consisted of manual annotated data and the affects we focused on were racism, aggression, and worries. Results indicate that even though measuring affects is a subjective process, machine learning is a promising way forward to analyze and measure the presence of different affects on hate forums.