[HTML][HTML] A systematic literature review on phishing website detection techniques

A Safi, S Singh - Journal of King Saud University-Computer and …, 2023 - Elsevier
Phishing is a fraud attempt in which an attacker acts as a trusted person or entity to obtain
sensitive information from an internet user. In this Systematic Literature Survey (SLR) …

Applications of deep learning for phishing detection: a systematic literature review

C Catal, G Giray, B Tekinerdogan, S Kumar… - … and Information Systems, 2022 - Springer
Phishing attacks aim to steal confidential information using sophisticated methods,
techniques, and tools such as phishing through content injection, social engineering, online …

Stop oversampling for class imbalance learning: A review

AS Tarawneh, AB Hassanat, GA Altarawneh… - IEEE …, 2022 - ieeexplore.ieee.org
For the last two decades, oversampling has been employed to overcome the challenge of
learning from imbalanced datasets. Many approaches to solving this challenge have been …

Deep learning for phishing detection: Taxonomy, current challenges and future directions

NQ Do, A Selamat, O Krejcar, E Herrera-Viedma… - Ieee …, 2022 - ieeexplore.ieee.org
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 …

Phishing email detection using natural language processing techniques: a literature survey

S Salloum, T Gaber, S Vadera, K Shaalan - Procedia Computer Science, 2021 - Elsevier
Phishing is the most prevalent method of cybercrime that convinces people to provide
sensitive information; for instance, account IDs, passwords, and bank details. Emails, instant …

Rdpvr: Random data partitioning with voting rule for machine learning from class-imbalanced datasets

AB Hassanat, AS Tarawneh, SS Abed, GA Altarawneh… - Electronics, 2022 - mdpi.com
Since most classifiers are biased toward the dominant class, class imbalance is a
challenging problem in machine learning. The most popular approaches to solving this …

Phishnot: A cloud-based machine-learning approach to phishing url detection

MM Alani, H Tawfik - Computer Networks, 2022 - Elsevier
Phishing is constantly growing to be one of the most adopted tools for conducting cyber-
attacks. Recent statistics indicated that 97% of users could not recognize a sophisticated …

Stock price forecasting for jordan insurance companies amid the covid-19 pandemic utilizing off-the-shelf technical analysis methods

GA Altarawneh, AB Hassanat, AS Tarawneh… - Economies, 2022 - mdpi.com
One of the most difficult problems analysts and decision-makers may face is how to improve
the forecasting and predicting of financial time series. However, several efforts were made to …

Sufficiency of ensemble machine learning methods for phishing websites detection

Y Wei, Y Sekiya - IEEE Access, 2022 - ieeexplore.ieee.org
Phishing is a kind of worldwide spread cybercrime that uses disguised websites to trick
users into downloading malware or providing personally sensitive information to attackers …

[HTML][HTML] Beyond the west: Revealing and bridging the gap between Western and Chinese phishing website detection

Y Yuan, G Apruzzese, M Conti - Computers & Security, 2025 - Elsevier
Phishing attacks are on the rise, and phishing websites are everywhere, denoting the
brittleness of security mechanisms reliant on blocklists. To cope with this threat, many works …