Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions

Autor: Nguyet Quang Do, Ali Selamat, Ondrej Krejcar, Enrique Herrera-Viedma, Hamido Fujita

Publikováno v: IEEE Access, Vol 10, Pp 36429-36463 (2022)

Phishing has become an increasing concern and captured the attention of end-users as well as security experts. Existing phishing detection techniques still suffer from the deficiency in performance accuracy and inability to detect unknown attacks des

Externí odkaz: https://doaj.org/article/fa906a7bbe7a48998fcbe785b4cb5bc4

Malicious URL Detection with Distributed Representation and Deep Learning

Autor: Nguyet Quang Do, Ali Selamat, Kok Cheng Lim, Ondrej Krejcar

There exist numerous solutions to detect malicious URLs based on Natural Language Processing and machine learning technologies. However, there is a lack of comparative analysis among approaches using distributed representation and deep learning. To s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::eec5191c5b268f4411e5edc39781bc57
https://doi.org/10.3233/faia220248

Phishing Webpage Classification via Deep Learning-Based Algorithms: An Empirical Study

Autor: Hamido Fujita, Ali Selamat, Takeru Yokoi, Nguyet Quang Do, Ondrej Krejcar

Publikováno v: Digibug. Repositorio Institucional de la Universidad de Granada
Consorcio Madroño
Applied Sciences
Volume 11
Issue 19
Applied Sciences, Vol 11, Iss 9210, p 9210 (2021)

This work was supported/funded by the Ministry of Higher Education under the Fundamental Research Grant Scheme (FRGS/1/2018/ICT04/UTM/01/1). The authors sincerely thank Universiti Teknologi Malaysia (UTM) under Research University Grant Vot-20H04, Ma

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0582f728884b26a7849d4c223da8a988
http://hdl.handle.net/10481/71233