Publications

@article{castano_familiarity_2024,

title = {Familiarity Analysis and Phishing Website Detection using PhiKitA Dataset [Póster]},

author = {Felipe Castaño and Alicia Martínez-Mendoza and Eduardo Fidalgo and Rocío Alaiz-Rodríguez and Enrique Alegre},

url = {https://idus.us.es/items/04850276-e785-4039-977b-0c43806ac349},

year  = {2024},

date = {2024-01-01},

abstract = {Phishing kits enable attackers to launch phishing campaigns more efficiently. This paper introduces PhiKitA, a dataset of phishing kits and the websites they generate. Three experiments were conducted: familiarity analysis, phishing website detection, and phishing kit classification, using MD5 hashes, fingerprints, and graph-based DOM representation. Results show that phishing website detection achieved 92.50% accuracy, while phishing kit classification proved less effective due to insufficient extracted information.},

note = {Publisher: Universidad de Sevilla. Escuela Técnica Superior de Ingeniería Informática},

keywords = {Cybersecurity, machine learning, PhinKitA Dataset, phishing detection},

pubstate = {published},

tppubtype = {article}

}