This study uses open source, public information to examine nation-state and non-nation-state ideologically motivated cyberattacks performed against US targets from 1998 to 2018. We created the Extremist Cyber Crime Database (ECCD) that includes scheme, offender and target codebooks to address gaps in existing research and better inform policymakers. We describe our open source collection procedures, the type of information uncovered, and how we assessed their quality and reliability. We highlight our findings, compare these extremist cyber-crimes to extremist real world violence, and discuss their conceptual and policy implications.

Target populations have always been a thorny issue for correctional programs, primarily in response to the question "what works for whom?" In this experiment of seamless treatment for probationers in two sites, offenders were randomly assigned to the seamless model (drug treatment incorporated into probation supervision) or traditional referral model to services in the community. The experiment blocked on risk level, using a version of the Wisconsin Risk Tool, to measure the differential effects on rearrest and substance abuse. The seamless system model improved treatment participation with greater gains for the high-risk offenders in both sites. Yet, no main effects were observed on drug use or rearrest, although effect sizes illustrate that small effects can be observed for the high-risk offenders and the direction of the effect size demonstrates negative effects for moderate-risk offenders in one of the sites. Part of the failure to observe main effects may be due to instrumentation and measurement problems, namely that many of the substance abusers in the experiment had low severity substance abuse problems and the majority of the offenders were marijuana users which has a weaker crime-drug linkage. Study findings illustrate the importance of theoretically driven and dynamic risk and need measures. The focus on sound dynamic factors may assist with identifying the appropriate target populations for correctional interventions.