Cyber Offending Among Young People: an Analysis of the Correlates for Different Categories of Cyber-Dependent Offending Using the Triple Risk Delinquency Framework

Abstract

Cyber-dependent offenses involve the exploitation of information technologies to target digital infrastructures, such as hacking, malware, and distributed denial-of service (DDoS) attacks. This study applied the Triple Risk Delinquency (TRD) framework as an analytical lens to compare personal, social, and situational or opportunity risks between distinct categories of cyber-dependent offending. We drew on data from a sample of 725 Dutch students aged 12–25 (Mage=16.62 years; SD = 1.99; 25.66% female) who were following IT programs, tracks, or courses in secondary or tertiary education. To address gaps in the existing literature on cyber-dependent crime, we first identified distinct subcategories of cyber-dependent offending using principal component analysis: (1) technical hacking, (2) using or creating technical tools, and (3) misuse of unauthorized access. Second, we aimed to identify and classify correlates associated with these categories, utilizing the TRD model as an organizing framework. Logistic regression models indicated that prior victimization and peer offending are consistently positively associated with all categories of cyber-dependent crime, underscoring their general significance as personal and social correlates. Offence-specific patterns emerged as well: higher IT knowledge was associated with technical hacking, whereas lower self-control was associated with misuse of unauthorized access. Opportunity risks (such as above average risky online activities) were more salient for technical hacking and tool use than for misuse of access, and stronger parental rules related negatively to technical hacking. The differences in correlates between these three categories underscore the need for future research that differentiates between different types of cyber dependent crime.