Document Type

Article

Abstract

We assess the severity of phishing attacks in terms of their risk levels and the potential loss in market value to the firms. We analyze 1,030 phishing alerts released on a public database as well as financial data related to the targeted firms using a hybrid text and data mining method that predicts the severity of the attack with high accuracy. Our research identifies the important textual and financial variables that impact the severity of the attacks and determine that different antecedents influence risk level and potential financial loss associated with phishing attacks.

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