This study investigates various factors that can affect the monetary impact of data breaches on companies. This paper introduces a model for the total cost of a mega data breach based on a data set created from multiple sources that categorises stolen data for U.S. residents as personally identifiable information (PII) and sensitive personally identifiable information (SPII). We use a rigorous stepwise regression analysis that includes polynomial and factorial multilevel effects of the independent variables. There are three significant findings. First, our model finds a significant relation between total data breach cost and revenue, the total amount of PII and SPII, and class action lawsuits. Second, the categorisation of personal information as sensitive and non-sensitive explains the cost better than previous work. Finally, all of the independent variables demonstrate multilevel factorial interactions.

这项研究调查了可能影响数据泄露对公司的金钱影响的各种因素。本文介绍了一种基于从多个来源创建的数据集的大型数据泄露总成本的模型，该数据集将美国居民的失窃数据归类为个人身份信息（PII）和敏感个人身份信息（SPII）。我们使用严格的逐步回归分析，其中包括自变量的多项式和阶乘多级效应。有三个重要发现。首先，我们的模型发现了数据泄露总成本与收入，PII和SPII的总金额以及集体诉讼之间的重要关系。其次，将个人信息分为敏感和不敏感类别比以前的工作更好地解释了成本。最后，