Forecasts of Electoral-Related Threats in 2022 Midterm Elections
This interactive dashboard presents a series of machine learning forecasts for different electoral-related threats ahead of the 2022 U.S. Midterm Elections.
Fighting the Hydra: Combatting Vulnerabilities in Online Leaderless Resistance Networks
Why do contemporary Racially-Motivated Violent Extremist (RMVE) movements champion “leaderless resistance,” and how can practitioners combat this organizational strategy? This report provides an overview of leaderless resistance networks, including their critical requirements, capabilities, and vulnerabilities. It assesses the effectiveness of different types of policy interventions given these vulnerabilities.
Emerging Security Risks in the Marine Transportation System, 2001-2021
How has maritime security evolved since 2001, and what challenges exist moving forward? This report provides an overview of the current state of maritime security with an emphasis on cybersecurity and violent extremist threats. It examines new cyber, technological, and extremist risks that have arisen over the last twenty years, the different types of security challenges these risks pose, and how practitioners can better navigate these challenges.
Predicting Domestic Extremism and Targeted Violence: A Machine Learning Approach
The report applies machine learning (ML) techniques to forecast where domestic extremist groups and active shooter incidents are most likely to occur in the United States. The model forecast a group’s area of operations with 96% accuracy and targeted violence incidents with 91% accuracy. The results suggest community-level risk factors are highly predictive of extremist operations and incidents.