Research on cyber-co-offending tends to focus on either the organizational structure of organized cybercrime or social learning processes among individuals. This paper provides a new perspective on co-offending by examining the extent to which individuals co-offend for different types of cybercrime compared to traditional crime. Additionally, differences in the type of co-offender (friends, family, or others) and relationships between IT- knowledge and cyber-co-offending are examined. This paper is based on individual self-report survey data from a judicial sample of Dutch adult cyber-dependent offenders and traditional offenders. It includes information on 466 different crimes (51.50% cybercrime) self-reported by 164 individuals. Results indicate that cybercrime and traditional crime show similar patterns of co-offending. The majority of offenders prefer to commit their crimes alone, but some types of crime are more often committed with co-offenders than other types of crime. For cybercrime results suggest that limitations in an offender’s IT-knowledge may be a reason to seek co-offenders with strong IT-skills.

In our highly digitalized society, cybercrime has become a common crime. However, because research into cybercriminals is in its infancy, our knowledge about cybercriminals is still limited. One of the main considerations is whether cybercriminals have higher intellectual capabilities than traditional criminals or even the general population. Although criminological studies clearly show that traditional criminals have lower intellectual capabilities, little is known about the relationship between cybercrime and intelligence. The current study adds to the literature by exploring the relationship between CITO-test scores and cybercrime in the Netherlands. The CITO final test is a standardized test for primary school students - usually taken at the age of 11 or 12 - and highly correlated with IQ-scores. Data from Statistics Netherlands were used to compare CITO-test scores of 143 apprehended cybercriminals with those of 143 apprehended traditional criminals and 143 non-criminals, matched on age, sex, and country of birth. Ordinary Least Squares regression analyses were used to compare CITO test scores between cybercriminals, traditional criminals, and non-criminals. Additionally, a discordant sibling design was used to control for unmeasured confounding by family factors. Findings reveal that cyber- criminals have significantly higher CITO test scores compared to traditional criminals and significantly lower CITO test scores compared to non-criminals.