This article describes the development of foreign fighters’ preparatory modes of operation between 2000 and 2013, based on an analysis of 17 closed police investigations and 21 semi-structured interviews with police investigators, public prosecutors, and lawyers. Through the use of grounded theory methods and a crime script analysis, we find that the phenomenon is not as new as is often portrayed. It changes over time as changing opportunity structures have an impact on the activities foreign fighters undertake during the preparation phase. We demonstrate how geopolitical changes, social opportunity structures, and technological developments affect themodus operandiover time. One of the implications of our findings is that the dynamic nature of the foreign fighting phenomenon requires flexible and tailored prevention measures.
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Prior research on network attacks is predominantly technical, yet little is known about behavioral patterns of attackers inside computer systems. This study adopts a criminological perspective to examine these patterns, with a particular focus on data thieves targeting organizational networks. By conducting interviews with cybersecurity experts and applying crime script analysis, we developed a comprehensive script that describes the typical progression of attackers through organizational systems and networks in order to eventually steal data. This script integrates phases identified in previous academic literature and expert-defined phases that resemble phases from industry threat models. However, in contrast to prior cybercrime scripts and industry threat models, we did not only identify sequential phases, but also illustrate the circular nature of network attacks. This finding challenges traditional perceptions of crime as a linear process. In addition, our findings underscore the importance of considering both successful and failed attacks in cybercrime research to develop more effective cybersecurity strategies.
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Hackers and Designers Summer AcademyThe Underdistanced and the UndernetworkedWorkshop script - draft 1
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Game development businesses often choose Lua for separating scripted game logic from reusable engine code. Lua can easily be embedded, has simple interfaces, and offers a powerful and extensible scripting language. Using Lua, developers can create prototypes and scripts at early development stages. However, when larger quantities of engine code and script are available, developers encounter maintainability and quality problems. First, the available automated solutions for interoperability do not take domain-specific optimizations into account. Maintaining a coupling by hand between the Lua interpreter and the engine code, usually in C++, is labour intensive and error-prone. Second, assessing the quality of Lua scripts is hard due to a lack of tools that support static analysis. Lua scripts for dynamic analysis only report warnings and errors at run-time and are limited to code coverage. A common solution to the first problem is developing an Interface Definition Language (IDL) from which ”glue code”, interoperability code between interfaces, is generated automatically. We address quality problems by proposing a method to complement techniques for Lua analysis. We introduce Lua AiR (Lua Analysis in Rascal), a framework for static analysis of Lua script in its embedded context, using IDL models and Rascal.
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Illicit data markets have emerged on Telegram, a popular online instant messaging application, bringing together thousands of users worldwide in an unregulated exchange of sensitive data. These markets operate through vendors who offer enormous quantities of such data, from personally identifiable information to financial data, while potential customers bid for these valuable assets. This study describes how Telegram data markets operate and discusses what interventions could be used to disrupt them. Using crime script analysis, we observed 16 Telegram meeting places encompassing public and private channels and groups. We obtained information about how the different meeting places function, what are their inside rules, and what tactics are employed by users to advertise and trade data. Based on the crime script, we suggest four feasible situational crime prevention measures to help disrupt these markets. These include taking down the marketplaces, reporting them, spamming and flooding techniques, and using warning banners. This is a post-peer-review, pre-copyedit version of an article published in Trends in organized crime . The final authenticated version is available online at https://doi.org/10.1007/s12117-024-09532-6
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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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Peerreview is een leeractiviteit waarbij studenten elkaar feedback geven. Uit onderzoek blijkt dat peerreview een leerproces effectief kan ondersteunen, maar alleen als het goed wordt georganiseerd. De onderzoekslijn Teaching, Learning & Technology doet daarom onderzoek naar de effectieve inzet van peerreview in leerprocessen. In deze factsheet gaan we in op het organiseren van peerreview. Dit wordt ook wel scripting van peerreview genoemd. Ons onderzoek heeft een script met zeven stappen opgeleverd. In deze factsheet worden de stappen beschreven. Daarbij wordt per stap aangeven wie wat doet op welke manier, en waar dat plaatsvindt.
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Peerreview is a learning activity in which students give eachother feedback. Research shows that peerreview can effectively support a learning process, but only if it is well organized. The research group Teaching, Learning & Technology conducts research into the effective use of peerreview in learning processes. This factsheet discusses the organization of peerreview, also known as ‘scripting’ of peerreview. Our research has resulted in a seven-step script. Each step indicates who does what, and where.
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De opleiding Business studies (BBS) organiseert het afstudeerproces via afstudeerkringen. De opleiding ervaart problemen bij het op gang brengen en productief maken van het samenwerkend leren tijdens de kringbijeenkomsten en daarbuiten. Daarnaast liggen er vraagstukken rondom het effectief inzetten van technologie om het samenwerkend leren binnen en buiten de kringbijeenkomsten te ondersteunen. Doel van dit onderzoek is het ontwerpen en testen van een (prototype)script van een effectieve inzet van samenwerkend leren binnen de met technologie ondersteunde afstudeerkringen. In dit rapport komen het vooronderzoek, de ontwerpfase en de evaluatiefase aan bod.
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