灾难框架中的数据泄露及其他
Data breaches in the catastrophe framework & beyond
摘要：
为网络风险开发可持续的保险，以及相关的好处，除其他外，需要减少风险的模糊性。考虑到网络风险，特别是数据泄露，作为一种人为的灾难，澄清了对多层次分析的精算需求-不仅仅是索赔驱动的损失统计数据，还包括风险敞口，危害，违规规模等-并且需要在数据和模型的范围，质量和标准方面取得具体进展。网络风险突出的人为因素，以及动态、网络化和多类型的性质，使其可能具有独特的挑战性。互补的自上而下的统计，自下而上的分析方法进行了讨论。专注于数据泄露的严重程度，在私人信息项目（“id”）提取测量，我们利用相对成熟的开放数据为美国的数据泄露。我们发现，这种极端的重尾风险正在恶化外部攻击者（“黑客”）事件-无论是在频率和严重性。在2018年第二季度的文章中，由于黑客攻击，2018年最后6个月美国入侵的id预测中值为5亿。但有5%的可能性，这一数字超过70亿-翻了一番的历史总数。“幸运的是”，这一时期的总违约率接近中位数。
英文摘要：
Development of sustainable insurance for cyber risks, with associated benefits, inter alia requires reduction of ambiguity of the risk. Considering cyber risk, and data breaches in particular, as a man-made catastrophe clarifies the actuarial need for multiple levels of analysis - going beyond claims-driven loss statistics alone to include exposure, hazard, breach size, and so on - and necessitating specific advances in scope, quality, and standards of both data and models. The prominent human element, as well as dynamic, networked, and multi-type nature, of cyber risk makes it perhaps uniquely challenging. Complementary top-down statistical, and bottom-up analytical approaches are discussed. Focusing on data breach severity, measured in private information items ('ids') extracted, we exploit relatively mature open data for U.S. data breaches. We show that this extremely heavy-tailed risk is worsening for external attacker ('hack') events - both in frequency and severity. Writing in Q2-2018, the median predicted number of ids breached in the U.S. due to hacking, for the last 6 months of 2018, is 0.5 billion. But with a 5% chance that the figure exceeds 7 billion - doubling the historical total. 'Fortunately' the total breach in that period turned out to be near the median.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
