Familiarity Analysis and Phishing Website Detection using PhiKitA Dataset [Póster]

Abstract

Phishing kits are tools used by phishers to deploy phishing attacks faster, more easily and on a larger scale. Detecting phishing kits could aid in the early detection of phishing campaigns by recognizing patterns resulting from the use of phishing kits in the creation of the attack. In this paper, we proposed a methodology to collect phishing kit data and created PhiKitA, a novel dataset that contains phishing kits and websites generated with them. Using PhiKitA, we performed three ex periments (familiarity analysis, phishing website detection, and multiclass classification of phishing kits) and evaluated three algorithms: MD5 hashes, fingerprints, and graph representation DOM. The first experiment shows evidence of different phishing kits, the second indicates that the algorithms retrieve useful information to detect phishing with an accuracy of 92.50%, and the third experiment indicates that the algorithms do not retrieve enough information to classify phishing.