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This study examines differences between users and nonusers of information communication technologies (ICTs) within the pre-incident planning processes for domestic terrorist movements operating within the United States. In addition, this study is the first quantitative exploration of the prevalence, types, and purposes of ICT use within terrorist movements, specifically environmental, far-right, and Islamic extremist movements. Using“officially designated” federal terrorism investigations from the American Terrorism Study (ATS), we analyzed extracted evidence of ICT usage among individuals (n =331) engaged in the pre-incident planning processes as members of terrorist movements between 1995-2011. While we find significant differences in terrorist ICT use across terrorist movements, our findings suggest that demographics are not a strong predictor of usage. We find the highest prevalence of usage among Islamic movements. However, evidence of online radicalization or recruitment was found predominantly among environmental movements. We conclude with a discussion of these findings and their implications for counterterrorism policy.

This dissertation explores the various online radicalization and recruitment practices of groups like al-Qaeda and Hezbollah, as well as Salafi Jihadists in general. I will also outline the inadequacies of the federal government’s engagement with terrorist / Islamist ideologies and explore the ways in which early 20th century foundational Islamist theorists like Hasan al-Banna, Sayyid Qutb, and Abul ala Mawdudi have affected contemporary extremist Islamist groups, while exploring this myth of the ideal caliphate which persists in the ideology of contemporary extremist Islamist groups. In a larger sense, I am arguing that exploitation of the internet (particularly social networking platforms) in the radicalization of new communities of followers is much more dangerous than cyberterrorism (as in attacks on cyber networks within the government and the private sector), which is what is most often considered to be the primary threat that terrorists pose with their presence on the internet. Online radicalization should, I argue, be given more consideration when forming public policy because of the immediate danger that it poses, especially given the rise of microterrorism. Similarly, through the case studies that I am examining, I am bringing the humanities into the discussion of extremist (religious) rhetorics, an area of discourse that those scholars have largely ignored.

The growing use of the Internet as a major means of communication has led to the formation of cyber-communities, which have become increasingly appealing to violent extremists due to the unregulated nature of Internet communication. Online communities enable violent extremists to increase recruitment by allowing them to build personal relationships with a worldwide audience capable of accessing uncensored content. This research presents methods for identifying and forecasting the recruitment activities of violent groups within extremist social media websites. Specifically, these methods employ techniques within supervised learning and natural language processing for automatically: (1) identifying forum posts intended to recruit new violent extremist members, and (2) forecasting recruitment efforts by tracking changes in an online community’s discussion over time. We used data from the western jihadist website Ansar AlJihad Network, which was compiled by the University of Arizona’s Dark Web Project. Multiple judges manually annotated a sample of these data, marking 192 randomly sampled posts as recruiting (Yes) or non-recruiting (No). We observed significant agreement between the judges’ labels; the confidence interval of Cohen’s kappa was (0.5,0.9) at p=0.01. We used naive Bayes models, logistic regression, classification trees, boosting, and support vector machines (SVM) to classify the forum posts in a 10-fold cross-validation experimental setup. Evaluation with receiver operating characteristic (ROC) curves show that our SVM classifier achieves 89% area under the curve (AUC), a significant improvement over the 63% AUC performance achieved by our simplest naive Bayes model (Tukey’s test at p=0.05). The forecasting task uses a time series regression analysis to model the daily count of extremist recruitment posts. Evaluation with mean absolute scaled error (MASE) shows that employing latent topics as predictors can reduce forecast error compared to a naive (random-walk) model and the baseline time series model. To our knowledge, these are the first results reported on these tasks, and our analysis indicates that automatic detection and forecasting of online terrorist recruitment are feasible tasks. This research could ultimately help identify the impact of violent organizations, like terrorist groups, within the social network of an online community. There are also a number of important areas of future work including classifying non-English posts and measuring how recruitment posts and current events change membership numbers over time.

International humanitarian law provides foundational norms which are to be observed by states in order to protect civilians from the harsh realities of war. These norms have been applied to traditional kinetic methods of warfare but as technology advances at a rapid pace so too do methods of warfare. As weaponry becomes more sophisticated it is necessary to revisit the foundational principles of international humanitarian law and apply them to situations that could only previously have been imagined. The principles of distinction is a core principle of this branch of law and it is not to be disregarded as a result of the fact that it predates modern methods of warfare but rather it is to be re-examined, its importance observed and applied to the warfare that we are faced with today. Protecting civilians has been of utmost importance in recent history and the development in the technology of weapons should not change that fact in the present or future.

As the Internet is progressively integrated into industrial and defense-related networks around the globe, it is becoming increasing important to understand how state and sub-state groups can use Internet vulnerabilities as a conduit of attack. The current social science literature on cyber threats is largely dominated by descriptive, U.S.-centric research. While this scholarship is important, the findings are not generalizable and fail to address the global aspects of network vulnerabilities. As a result, this dissertation employs a unique dataset of cyber threats from around the world, spanning from 1990 to 2011. This dataset allows for three diverse empirical studies to be conducted. The first study investigates the political, social, and economic characteristics that increase the likelihood of a state being targeted for cyber threats. The results show that different state characteristics are likely to influence the forms of digital attack targeting. For example, states that experience increases in GDP per capita and military size are more likely to be targeted for cyber attacks. Inversely, states that experience increases in GDP per capita and those that are more democratic are less likely to be targeted for cyber terrorism. The second study investigates the role that international rivalries play in cyber threat targeting. The results suggest that states in rivalries may have more reason to strengthen their digital security, and rival actors may be cautious about employing serious, threatening forms of cyber activity against foes because of concerns about escalation. The final study, based upon the crisis bargaining theory, seeks to determine if cyber threat targeting decreases private information asymmetry and therefore decreases conflict participation. Empirical results show that the loss of digital information via cyber means may thus illicit a low intensity threat or militarized action by a target state, but it also simultaneously increases the likelihood that a bargain may be researched, preventing full scale war by reducing the amount of private information held between parties.

VOX-Pol Blog post.