While traditional crime rates are decreasing, cybercrime is on the rise. As a result, the criminal justice system is increasingly dealing with criminals committing cyber-dependent crimes. However, to date there are no effective interventions to prevent recidivism in this type of offenders. Dutch authorities have developed an intervention program, called Hack_Right. Hack_Right is an alternative criminal justice program for young first-offenders of cyber-dependent crimes. In order to prevent recidivism, this program places participants in organizations where they are taught about ethical hacking, complete (technical) assignments and reflect on their offense. In this study, we have evaluated the Hack_Right program and the pilot interventions carried out thus far. By examining the program theory (program evaluation) and implementation of the intervention (process evaluation), the study adds to the scarce literature about cybercrime interventions. During the study, two qualitative research methods have been applied: 1) document analysis and 2) interviews with intervention developers, imposers, implementers and participants. In addition to the observation that the scientific basis for linking specific criminogenic factors to cybercriminals is still fragile, the article concludes that the theoretical base and program integrity of Hack_Right need to be further developed in order to adhere to principles of effective interventions.
Crime script analysis as a methodology to analyse criminal processes is underdeveloped. This is apparent from the various approaches in which scholars apply crime scripting and present their cybercrime scripts. The plethora of scripting methods raise significant concerns about the reliability and validity of these scripting studies. In this methodological paper, we demonstrate how object-oriented modelling (OOM) could address some of the currently identified methodological issues, thereby refining crime script analysis. More specifically, we suggest to visualise crime scripts using static and dynamic modelling with the Unified Modelling Language (UML) to harmonise cybercrime scripts without compromising their depth. Static models visualise objects in a system or process, their attributes and their relationships. Dynamic models visualise actions and interactions during a process. Creating these models in addition to the typical textual narrative could aid analysts to more systematically consider, organise and relate key aspects of crime scripts. In turn, this approach might, amongst others, facilitate alternative ways of identifying intervention measures, theorising about offender decision-making, and an improved shared understanding of the crime phenomenon analysed. We illustrate the application of these models with a phishing script.
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