The psychological correlates of cybercrime offending: Exploring the self-control/social learning relationship in serious cyber-dependent crime

Abstract

This study sought to explore the relationship between low self-control, social learning, and serious forms of cybercrime offending. Using general population survey data from 1240 Dutch young people, we ran a series of binary logistic regression models to estimate the role of various risk variables for engaging in four cyber-dependent crimes: guessing passwords, DoS/DDoS attacks, hacking with technological means, and website defacements. The analysis identified distinct patterns for the various offending behaviors: more simple forms related to low self-control, although this relationship disappeared when accounting for social learning. In contrast, more serious cybercrime behaviors were associated with higher levels of self-control but only when including social learning variables, hinting at a possible suppression effect. This means that the general theory of crime may not be able to explain complex forms of cybercrime. Rather, these behaviors are enmeshed in online and offline social environments, putting at risk those young people who are equipped with the necessary capabilities and patience to learn.