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Cybercrime is a major challenge facing the world, with estimated costs ranging from the hundreds of millions to the trillions. Despite the threat it poses, cybercrime is somewhat an invisible phenomenon. In carrying out their virtual attacks, offenders often mask their physical locations by hiding behind online nicknames and technical protections. This means technical data are not well suited to establishing the true location of offenders and scholarly knowledge of cybercrime geography is limited. This paper proposes a solution: an expert survey. From March to October 2021 we invited leading experts in cybercrime intelligence/investigations from across the world to participate in an anonymized online survey on the geographical location of cybercrime offenders. The survey asked participants to consider five major categories of cybercrime, nominate the countries that they consider to be the most significant sources of each of these types of cybercrimes, and then rank each nominated country according to the impact, professionalism, and technical skill of its offenders. The outcome of the survey is the World Cybercrime Index, a global metric of cybercriminality organised around five types of cybercrime. The results indicate that a relatively small number of countries house the greatest cybercriminal threats. These findings partially remove the veil of anonymity around cybercriminal offenders, may aid law enforcement and policymakers in fighting this threat, and contribute to the study of cybercrime as a local phenomenon. [ABSTRACT FROM AUTHOR]

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The paper provides a theoretical framework for categorizing organized crime groups based on what they do – whether they produce, trade or govern – as well as their aims. This paper then tests whether the internal structure of a heroin distribution organization in New York City, a Sicilian mafia group and the Provisional Irish Republican Army differ. Applying Exponential Random Graph Models (ERGMs) methods to network data, we find the organizational structure of trade-type organized crime differs markedly from governance-type, as well as between financially-motivated and politically-motivated groups. Trade-type organized crime and financially-motivated groups display a high level of centralization, an even distribution of clustering values, short paths and low homophily. Governance-type organized crime and politically-motivated groups display the opposite features. We conclude that the core activity and aim of the group are crucial in understanding the organizational structure. [ABSTRACT FROM AUTHOR]