Predicting the Occurrence of a Data Breach
Mehdi Barati, Benjamin Yankson
Abstract
The problem of data breach incidents is prevalent in the media and has attracted the attention of researchers and practitioners working diligently on solutions. Commercial entities, non-profit organizations, and government agencies that obtain, process, and store personal or business-related information face the risks of the breach of client personal information and organizational intellectual property, which can result in legal, reputational, and financial damages. This study aims to estimate the probability of the occurrence of a breach and its size using a predictive model with historical data as input. We used a dataset of all reported data breaches in the U.S. collected by Privacy Rights Clearinghouse (PRC). The results show that the trend of data breaches has not been increasing despite all the attention and warnings. Our Poisson and Negative binomial models proved promising and can predict data breach incidents with low deviance from actual numbers.