Business email compromise phishing detection based on machine learning: a systematic literature review

HF Atlam, O Oluwatimilehin - Electronics, 2022 - mdpi.com
The risk of cyberattacks against businesses has risen considerably, with Business Email
Compromise (BEC) schemes taking the lead as one of the most common phishing attack …

An investigation into the performances of the Current state-of-the-art Naive Bayes, Non-Bayesian and Deep Learning Based Classifier for Phishing Detection: A …

T Ige, C Kiekintveld, A Piplai, A Waggler… - arxiv preprint arxiv …, 2024 - arxiv.org
Phishing is one of the most effective ways in which cybercriminals get sensitive details such
as credentials for online banking, digital wallets, state secrets, and many more from potential …

Helphed: Hybrid ensemble learning phishing email detection

P Bountakas, C Xenakis - Journal of network and computer applications, 2023 - Elsevier
Phishing email attack is a dominant cyber-criminal strategy for decades. Despite its
longevity, it has evolved during the COVID-19 pandemic, indicating that adversaries exploit …

Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning

MA Tamal, MK Islam, T Bhuiyan, A Sattar… - Frontiers in Computer …, 2024 - frontiersin.org
Introduction The dynamic and sophisticated nature of phishing attacks, coupled with the
relatively weak anti-phishing tools, has made phishing detection a pressing challenge. In …

Phishing URLs detection using sequential and parallel ML techniques: comparative analysis

N Nagy, M Aljabri, A Shaahid, AA Ahmed, F Alnasser… - Sensors, 2023 - mdpi.com
In today's digitalized era, the world wide web services are a vital aspect of each individual's
daily life and are accessible to the users via uniform resource locators (URLs) …

[HTML][HTML] The applicability of a hybrid framework for automated phishing detection

RJ van Geest, G Cascavilla, J Hulstijn, N Zannone - Computers & Security, 2024 - Elsevier
Phishing attacks are a critical and escalating cybersecurity threat in the modern digital
landscape. As cybercriminals continually adapt their techniques, automated phishing …

A feature-based robust method for abnormal contracts detection in ethereum blockchain

A Aljofey, A Rasool, Q Jiang, Q Qu - Electronics, 2022 - mdpi.com
Blockchain technology has allowed many abnormal schemes to hide behind smart
contracts. This causes serious financial losses, which adversely affects the blockchain …

Life-long phishing attack detection using continual learning

A Ejaz, AN Mian, S Manzoor - Scientific Reports, 2023 - nature.com
Phishing is an identity theft that employs social engineering methods to get confidential data
from unwary users. A phisher frequently attempts to trick the victim into clicking a URL that …

A lightweight multi-view learning approach for phishing attack detection using transformer with mixture of experts

Y Wang, W Ma, H Xu, Y Liu, P Yin - Applied Sciences, 2023 - mdpi.com
Phishing poses a significant threat to the financial and privacy security of internet users and
often serves as the starting point for cyberattacks. Many machine-learning-based methods …

[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 …