Assessing the severity of phishing attacks: A hybrid data mining approach

Abstract

Phishing is an online crime that increasingly plagues firms and their consumers. We assess the severity of phishing attacks in terms of their risk levels and the potential loss in market value suffered by the targeted firms. We analyze 1030 phishing alerts released on a public database as well as financial data related to the targeted firms using a hybrid method that predicts the severity of the attack with up to 89% accuracy using text phrase extraction and supervised classification. Our research identifies some important textual and financial variables that impact the severity of the attacks and potential financial loss. © 2010 Elsevier B.V. All rights reserved.