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Posts tagged cybercriminal
Cybercrime: The Transformation of Crime in the Information Age

MAY CONTAIN MARKUP

BY DAVID S. WALL

Looking at the full range of cybercrime, and computer security he shows how the increase in personal computing power available within a globalized communications network has affected the nature of and response to criminal activities. We have now entered the world of low impact, multiple victim crimes in which bank robbers, for example, no longer have to meticulously plan the theft of millions of dollars. New technological capabilities at their disposal now mean that one person can effectively commit millions of robberies of one dollar each. Against this background, David Wall scrutinizes the regulatory challenges that cybercrime poses for the criminal (and civil) justice processes, at both the national and the international levels.

Polity, 2007, 276 pages

The Effect of COVID‑19 Restrictions on Routine Activities and Online Crime 

By Shane D. Johnson and  Manja Nikolovska

Objectives Routine activity theory suggests that levels of crime are affected by peoples’ activity patterns. Here, we examine if, through their impact on people’s on- and off-line activities, COVID-19 restriction affected fraud committed on- and off-line during the pandemic. Our expectation was that levels of online offending would closely follow changes to mobility and online activity—with crime increasing as restrictions were imposed (and online activity increased) and declining as they were relaxed. For doorstep fraud, which has a different opportunity structure, our expectation was that the reverse would be true. Method COVID-19 restrictions systematically disrupted people’s activity patterns, creating quasi-experimental conditions well-suited to testing the effects of “interventions” on crime. We exploit those conditions using ARIMA time series models and UK data for online shopping fraud, hacking, doorstep fraud, online sales, and mobility to test hypotheses. Doorstep fraud is modelled as a non-equivalent dependent variable, allowing us to test whether findings were selective and in line with theoretical expectations. Results After controlling for other factors, levels of crime committed online were positively associated with monthly variation in online activities and negatively associated with monthly variation in mobility. In contrast, and as expected, monthly variation in doorstep fraud was positively associated with changes in mobility. Conclusions We find evidence consistent with routine activity theory, suggesting that disruptions to people’s daily activity patterns afect levels of crime committed both on- and off-line. The theoretical implications of the findings, and the need to develop a better evidence base about what works to reduce online crime, are discussed. 

Journal of Quantitative Criminology, 2022.

Understanding cybercriminal behaviour among young people: Results from a longitudinal network study among a relatively high-risk sample

By Marleen Weulen Kranenbarg, Yaloe van der Toolen, Frank Weerman.

This report aims to increase our insight into the explanation of cyber-delinquency among juveniles. We examined which individual characteristics and environmental factors are related to different types of cybercrime, with a specific focus on the importance of peer relationships. We used a longitudinal research design (three waves of data collection) among a substantial sample of Dutch youths in secondary or tertiary education (with ages between 12 and 25), who were following ICT programmes, tracks, or courses. These students were chosen because they are considered to be at an elevated risk of committing cybercrime. We used questionnaires to collect self-report data on a large variety of cyber-offences, and on characteristics of both offline and online peers. We distinguished between cyber-dependent offending (i.e. offences requiring the use of online means) and cyber-enabled offending (i.e. offences existing in the offline world, but that can also be conducted online). We also included questions about common traditional types of offending. In addition, we asked the respondents about various individual characteristics and environmental factors and we collected detailed social network data on the respondents’ school friends. Our methods (for details, see Chapter 3) addressed various important limitations in previous research on cyberdelinquency (see Chapter 2).

Amsterdam: VU University Amsterdam/Netherlands Institute for the Study of Crime and Law Enforcement, 2022. 107p.