TAILORING VIOLENT EXTREMISM PREVENTION: A TARGETED INTERVENTION METHOD

Abstract

The threat that emanates from violent extremism in the United States has shifted from large-scale networked cells to lone-wolf attackers. These violent extremists vary in ethnicity, race, age, religion, and motivations, and their path to radicalization is not linear. However, the majority of Department of Homeland Security programs designed to combat violent extremism still focus exclusively on the Muslim population and on community-based approaches. This thesis identifies two separate but related deficiencies in current countering violent extremism (CVE) programs: first, their inability to prevent attacks perpetrated by individuals who have been interviewed by law enforcement but did not become subjects of a formal investigation, and second, their inability to provide early intervention for individuals who are vulnerable to radicalization. This research proposes a multi-disciplinary, comprehensive model to prevent violent extremism at every intervention point, leveraging law enforcement capabilities, neighborhood policing models, and more robust threat assessment methods.