Cyberspace is a new spatial realm of activities involving both humans and data, and it has become a cornerstone of the national security of every country. A scientific understanding of cyberspace is essential for analyzing cyberspace incidents, governing cyberspace and ensuring cybersecurity. Accordingly, cyberspace has become a new field of geographic research in the Information Age. Against the backdrop of fierce international competition over cyberspace, there has been an urgent need to strengthen research between the fields of geography and cybersecurity, leading to theoretical and methodological innovations that have created the sub-discipline of cyberspace geography. Cyberspace geography (CG) extends geographical research from real spaces to virtual spaces, and its theoretical basis is the evolution of the traditional geographic human-land relationship theory into a human-land-network relationship theory. CG research includes constructing mapping relationships between cyberspace and real space, redefining the traditional geographic concepts of distance and regions for cyberspace, creating a language, models and methodologies for visually representing cyberspace, drawing maps of cyberspace, and researching the principles governing the evolution of cyberspace structures and behaviors. The technical methods of CG include collecting and integrating data on elements of cyberspace, visually representing cyberspace and conducting cyberspace situational and behavioral intelligence awareness. Intelligence awareness covers cyberspace situational status assessments, network hotspot event dissemination and traceability analysis, and network event situational simulations and risk predictions. CG offers new perspectives on the scientific understanding of cyberspace, the development of disciplines such as geography and cybersecurity, and the creation of national cybersecurity prevention and control mechanisms as well as a community of common future in cyberspace.

Cybercrime is wreaking havoc on the global economy, national security, social stability, and individual interests. The current efforts to mitigate cybercrime threats are primarily focused on technical measures. This study considers cybercrime as a social phenomenon and constructs a theoretical framework that integrates the social, economic, political, technological, and cybersecurity factors that influence cybercrime. The FireHOL IP blocklist, a novel cybersecurity data set, is used to map worldwide subnational cybercrimes. Generalised linear models (GLMs) are used to identify the primary factors influencing cybercrime, whereas structural equation modelling (SEM) is used to estimate the direct and indirect effects of various factors on cybercrime. The GLM results suggest that the inclusion of a broad set of socioeconomic factors can significantly improve the model’s explanatory power, and cybercrime is closely associated with socioeconomic development, while their effects on cybercrime differ by income level. Additionally, results from SEM further reveals the causal relationships between cybercrime and numerous contextual factors, demonstrating that technological factors serve as a mediator between socioeconomic conditions and cybercrime.

As a typical cybercrime, cyber fraud poses severe threats to civilians’ property safety and social stability. Traditional criminological theories such as routine activity theory focus mainly on the effects of individual characteristics on cybercrime victimization and ignore the impacts of macro-level environmental factors. This study aims at exploring the spatiotemporal pattern of cyber fraud crime in China and investigating the relationships between cyber fraud and environmental factors. The results showed that cyber fraud crimes were initially distributed in southeastern China and gradually spread towards the middle and northern regions; spatial autocorrelation analysis revealed that the spatial concentration trend of cyber fraud became more and more strong, and a strong distinction in cyber fraud clustering between the north and the south was identified. To further explain the formative causes of these spatial patterns, a generalized additive model (GAM) was constructed by incorporating natural and social environmental factors. The results suggested that the distribution of cyber fraud was notably affected by the regional economy and population structure. Also, the high incidence of cyber fraud crime was closely associated with a large nonagricultural population, a high proportion of tertiary industry in GDP, a large number of general college students, a longer cable length, and a large numbers of internet users.