面對缺乏網絡保險損失資料的情況，我們提出了一種基于合成資料的大型網絡網絡保險定價方法的創新方法。通過建議的風險分散和恢複算法生成綜合資料，該算法允許感染和恢複事件順序發生，并允許随機等待時間依賴于不同節點的感染。采用無标度網絡架構來考慮随機大規模網絡的拓撲不确定性。我們進行了大量的模拟研究，以了解風險的擴散和恢複機制，并揭示最重要的承保風險因素。還提供了一個案例研究，以證明所提出的方法和算法可以進行相應的調整，以為網絡保險定價提供參考。
原文題目：Pricing cyber insurance for a large-scale network
原文：Facing the lack of cyber insurance loss data, we propose an innovative approach for pricing cyber insurance for a large-scale network based on synthetic data. The synthetic data is generated by the proposed risk spreading and recovering algorithm that allows infection and recovery events to occur sequentially, and allows dependence of random waiting time to infection for different nodes. The scale-free network framework is adopted to account for the topology uncertainty of the random large-scale network. Extensive simulation studies are conducted to understand the risk spreading and recovering mechanism, and to uncover the most important underwriting risk factors. A case study is also presented to demonstrate that the proposed approach and algorithm can be adapted accordingly to provide reference for cyber insurance pricing.
原文作者：Lei Hua, Maochao Xu
原文位址：https://arxiv.org/abs/2007.00454
大型網絡的網絡保險定價（CS SI）.pdf