Cybercrime is becoming ever more pervasive and yet the lack of consensus surrounding what constitutes a cybercrime has a significant impact on society, legal and policy response, and academic research. Difficulties in understanding cybercrime begin with the variability in terminology and lack of consistency in cybercrime legislation across jurisdictions. In this review, using a structured literature review methodology, key cybercrime definitions, typologies and taxonomies were identified across a range of academic and non-academic (grey literature) sources. The findings of this review were consolidated and presented in the form of a new classification framework to understand cybercrime and cyberdeviance. Existing definitions, typologies and taxonomies were evaluated, and key challenges were identified. Whilst conceptualizing cybercrime will likely remain a challenge, this review provides recommendations for future work to advance towards a universal understanding of cybercrime phenomena as well as a robust and comprehensive classification system.

Adolescents are currently the most digitally connected generation in history. There is an ever-growing need to understand how typical adolescent risk-taking intersects with the vastly criminogenic potential of digital technology. Criminal hacking in older adolescents (16–19-year-olds) was assessed using an adapted Theory of Planned Behaviour (TPB) model, a cohesive theoretical framework that incorporates cognitive processes and human drivers (informed by psychology, cyberpsychology, and criminology theory). In 2021, a large-scale anonymous online survey was conducted across nine European countries. Criminal hacking was assessed using data from 3985 participants (M = 1895, 47.55%; F = 1968, 49.39%). This study formulated a powerful predictive model of youth hacking intention (accounting for 38.8% of the variance) and behaviour (accounting for 33.6% of the variance). A significant minority, approximately one in six (16.34%), were found to have engaged in hacking, and approximately 2% reported engaging in hacking often or very often. Increased age, being male, and offline deviant behaviour were significant predictors of hacking behaviour. In line with the TPB, intention was the strongest individual predictor of hacking behaviour, which in turn was significantly predicted by cognitive processes accounted for by TPB constructs: subjective norms of family and peers, attitudes towards hacking, and perceived behavioural control. These TPB constructs were found to be significantly associated with human factors of risk-taking, toxic online disinhibition, offline deviant behaviour, and demographic variables of age and gender. Implications for future research, interventions, policy, and practice are discussed.