Scant research has investigated the illicit online ecosystem that enables the sale of stolen data. Even fewer studies have examined the longitudinal trends of the markets on which these data are bought and sold. To fill this gap in the literature, our research team identified 30 darknet markets advertising stolen data products from September 1, 2020, through April 30, 2021. We then developed python web scrapers to systematically extract information pertaining to stolen data products on a weekly basis. Using these data, we calculated the number of vendors, listings, sales, and revenue across the markets and at the aggregate, ecosystem level. Moreover, we developed a data-driven market classification system drawing from ecological principles and dominant firm theory. Findings indicate that markets vary in size and success. Although some markets generated over $91 million in revenue from stolen data products, the median revenue across markets during the observational period was only $95,509. Variability also exists across markets in respect to the number of vendors, listings, and sales. Only three markets were classified as financially successful and stable (i.e., dominant firms). We argue resources should be allocated to target markets fitting these criteria.

Given the victim-offender overlap, it has been suggested that every theory about offenders implies a corresponding theory of victimization. We assess the above assertion concerning Agnew’s general theory of crime and delinquency within the context of intimate partner violence (IPV). Drawing data from the International Dating Violence Study, we examine the direct and indirect effects of the self, family, school/work, and peer domains on IPV perpetration and victimization. We found the four life domains significantly predicted both IPV perpetration and victimization and their effects on both outcome variables were mediated by the constraint and motivation factors. Our results indicate that the mechanisms that account for offending posited in Agnew’s perspective appear to be equally relevant and applicable for understanding victimization.

Neighborhood characteristics are important considerations when offenders make targeting decisions. Movement patterns among adults and juveniles vary widely, which impacts both the number of crime opportunities and the range of neighborhoods to which an offender is exposed. We test whether offending patterns among adult and juvenile burglars vary based on distances traveled, the types of neighborhoods targeted, and whether suspects acted alone or in a group. Using discrete choice modeling, we draw upon a unique sample of cleared burglaries in a representative city in the south over a 13-year period. Results show that adult burglars consistently travel further and are more sensitive to neighborhood conditions than their juvenile counterparts, but that group participation makes little difference in target decisions.

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