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

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.

Research highlights
► Risk level and CAR level were complementary severity measures for phishing attacks.
► Using textual data and financial data make the severity prediction more accurate.
► Data mining techniques are effective to assess severity of phishing attacks.