Exploring the global geography of cybercrime and its driving forces

Shuai Chen, Mengmeng Hao, Fangyu Ding, Dong Jiang (), Jiping Dong, Shize Zhang, Qiquan Guo and Chundong Gao
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Shuai Chen: Chinese Academy of Sciences
Mengmeng Hao: Chinese Academy of Sciences
Fangyu Ding: Chinese Academy of Sciences
Dong Jiang: Chinese Academy of Sciences
Jiping Dong: Chinese Academy of Sciences
Shize Zhang: Big Data Center of State Grid Corporation of China
Qiquan Guo: Chinese Academy of Sciences
Chundong Gao: The Administrative Bureau of Chinese Academy of Sciences

Palgrave Communications, 2023, vol. 10, issue 1, 1-10

Abstract: Abstract 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.

Date: 2023
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DOI: 10.1057/s41599-023-01560-x

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