SAGE Journal Articles

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Journal Article 1: Roth, J. J. (2018). Property crime clearance in small jurisdictions: Police and community factors. Criminal Justice Review, 43, 477–493.

Abstract: Research on the factors that influence crime clearance rates has primarily studied violent crimes in large cities. However, property crimes are among the most commonly occurring and least frequently cleared offenses, and the majority of police departments in the United States serve small jurisdictions. Thus, this study undertook an examination of the predictors of clearance rates for burglary, larceny, and vehicle theft in a sample of agencies serving populations of 50,000 people or fewer. Independent variables included both policing factors (e.g., workload, funding, broken windows arrests) and social disorganization indicators (e.g., residential instability, poverty). Negative binomial regression analyses revealed variation in the significance of the predictors across the three crimes. Additionally, many predictors found to be influential in prior work were insignificant in this study, which suggests differences in the nature of crime clearance between large cities and smaller jurisdictions and a need for further research in this area.

Journal Article 2: Custers, B. H. M., Pool, R. L. D., & Cornelisse, R. (2018). Banking malware and the laundering of its profits. European Journal of Criminology.

Abstract: Banking malware is malicious software that aims to steal money from victims via manipulated bank transfers in online banking. This paper describes how the profits of banking malware are generated and subsequently laundered, with a particular focus on the use of bitcoins and other digital payment methods. Computers are infected with banking malware via phishing emails, in which people are persuaded in various ways to click on links or open attachments, or via exploit kits, programs that try to find weak spots in the security of computer systems. After infection, bank transfers of the online banking accounts of victims are manipulated via fake website screens (web injects). Behind the screens the amounts and beneficiaries of transactions are modified, emptying the victims’ bank accounts. In the next step, the banking malware profits are laundered. In this paper we describe two models that are used in particular (next to more traditional money laundering methods). The first model involves the use of money mules and a quick cash-out. The second model focuses on direct spending via (a) direct purchases of products via online shopping, (b) direct purchases of bitcoins via Bitcoin exchanges or (c) direct purchases of luxury goods. Bitcoins can be further laundered via so-called mixing services. All in all, these methods allow criminals to launder profits in relative anonymity and prevent seizure of the illegal profits.