Abstract
In this paper, we investigate the likelihood of cyber-attacks targeted on publicly listed companies. By reviewing the complete financial statements of the attacked companies through CompStat North America and information of cyber-attack incidents through Privacy Rights Clearinghouse, we process hundreds of the financial features in the statements to analyze the likelihood of cyber-attacks to the cohort of listed large public companies. After assessing multiple modified training models by using logistic regression, the patterns between financial features and likelihood of cyber-attacks are established. Key financial features that are highly correlated to cyber-attacks are identified.
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