A network-based distributional inference approach to model country-level cyber risk
利用社交网络中的Wasserstein传播，提出一种分布框架来推断各国网络风险，揭示国家间的相互依赖和脆弱性，为全球网络安全政策提供见解。
Abstract This article leverages Wasserstein Propagation in Social Network to propose a novel distributional framework for the inference of cyber risk across interconnected economic systems. Cyber attacks represent an increasing threat to global security and economic stability, making the assessment of cyber risk particularly challenging, especially in countries with limited data availability. Using a comprehensive dataset on worldwide cyber attacks along with a set of macroeconomic indicators, we estimate risk profiles for all countries, including those with sparse information. Our approach reveals critical interdependencies and vulnerabilities among countries, highlighting the interconnected nature of cyber risks. The findings demonstrate the value of social network analysis in modelling cyber risk and the related uncertainty within cyberspace. Furthermore, the results offer actionable insights to strengthen global cybersecurity policies and improve resilience against cyber threats.