Publications

@article{martinez_mendoza_novel_2023,

title = {Novel benchmark dataset and features to detect phishing on web pages},

author = {Alicia Martínez Mendoza and Manue Sánchez Paniagua and Francisco Jañez Martino and Rocío Aláiz Rodríguez and Eduardo Fidalgo and Enrique Alegre},

url = {https://dialnet.unirioja.es/servlet/articulo?codigo=9057251},

year  = {2023},

date = {2023-01-01},

journal = {Actas de las VIII Jornadas Nacionales de Investigación en Ciberseguridad: Vigo, 21 a 23 de junio de 2023},

pages = {599–600},

abstract = {Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023},

note = {Publisher: Universidade de Vigo},

keywords = {Phishing, web pages},

pubstate = {published},

tppubtype = {article}

}

@article{gangwar_phishfingerprint_2018,

title = {Phishfingerprint: A practical approach for phishing web page identity retrieval based on visual cues},

author = {Abhishek Gangwar and Eduardo Fidalgo and Enrique Alegre and Vıctor González-Castro},

url = {https://scholar.google.es/citations?view_op=view_citation&hl=en&user=opCbArQAAAAJ&cstart=100&pagesize=100&sortby=title&citation_for_view=opCbArQAAAAJ:XiSMed-E-HIC},

year  = {2018},

date = {2018-01-01},

journal = {International Conference of Applications of Intelligent Systems},

abstract = {This paper proposes a framework to maintain a repository of phishing web pages and retrieve the identity of newly reported phishing pages. The framework has two key contributions: first, it introduces a semi-automated method to create a non-redundant database of phishing websites. Second, it presents a robust two-stage approach to identify the reported phishing page by comparing its visual similarity to the registered pages using perceptual hash fingerprinting.},

keywords = {Cybersecurity, Perceptual Hash, Phishing, Visual Similarity},

pubstate = {published},

tppubtype = {article}

}