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Phishing or Not Phishing? A Survey on the Detection of Phishing Websites

Articolo
Data di Pubblicazione:
2023
Abstract:
Phishing is a security threat with serious effects on individuals as well as on the targeted brands. Although this threat has been around for quite a long time, it is still very active and successful. In fact, the tactics used by attackers have been evolving continuously in the years to make the attacks more convincing and effective. In this context, phishing detection is of primary importance. The literature offers many diverse solutions that cope with this issue and in particular with the detection of phishing websites. This paper provides a broad and comprehensive review of the state of the art in this field by discussing the main challenges and findings. More specifically, the discussion is centered around three important categories of detection approaches, namely, list-based, similarity-based and machine learning-based. For each category we describe the detection methods proposed in the literature together with the datasets considered for their assessment and we discuss some research gaps that need to be filled.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Security threat, phishing website, phishing detection, URL, blacklists, machine learning, page similarity, datasets, social engineering
Elenco autori:
Zieni, R; Massari, L; Calzarossa, M
Autori di Ateneo:
CALZAROSSA MARIA
MASSARI LUISA
ZIENI Rasha
Link alla scheda completa:
https://iris.unipv.it/handle/11571/1477533
Pubblicato in:
IEEE ACCESS
Journal
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