Detecting malicious URLs using machine learning techniques: review and research directions

M Aljabri, HS Altamimi, SA Albelali, M Al-Harbi… - IEEE …, 2022 - ieeexplore.ieee.org
In recent years, the digital world has advanced significantly, particularly on the Internet,
which is critical given that many of our activities are now conducted online. As a result of …

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 …

Phishing and intrusion attacks: An overview of classification mechanisms

S Tareen, SU Bazai, S Ullah, R Ullah… - 2022 3rd …, 2022 - ieeexplore.ieee.org
The digital world is becoming increasingly interconnected and cyberattacks such as
phishing are becoming more common. Fraudulent emails and bogus websites are used to …

Application of word embedding and machine learning in detecting phishing websites

RS Rao, A Umarekar, AR Pais - Telecommunication Systems, 2022 - Springer
Phishing is an attack whose aim is to gain personal information such as passwords, credit
card details etc. from online users by deceiving them through fake websites, emails or any …

Qsecr: Secure qr code scanner according to a novel malicious url detection framework

AS Rafsanjani, NB Kamaruddin, HM Rusli… - IEEE …, 2023 - ieeexplore.ieee.org
Malicious Uniform Resource Locators (URLs) are the major issue posed by cybersecurity
threats. Cyberattackers spread malicious URLs to carry out attacks such as phishing and …

[PDF][PDF] Machine learning and deep learning based phishing websites detection: The current gaps and next directions

K Adane, B Beyene - Review of Computer Engineering Research, 2022 - academia.edu
To compete with the rest of the world, every country is relying on the internet for cashless
transactions, online commerce, paperless tickets, and other productivity methods. Phishing …

Single and hybrid-ensemble learning-based phishing website detection: examining impacts of varied nature datasets and informative feature selection technique

K Adane, B Beyene, M Abebe - Digital Threats: Research and Practice, 2023 - dl.acm.org
To tackle issues associated with phishing website attacks, the study conducted rigorous
experiments on RF, GB, and CATB classifiers. Since each classifier was an ensemble …

[HTML][HTML] Phishing URL detection generalisation using Unsupervised Domain Adaptation

F Rashid, B Doyle, SC Han, S Seneviratne - Computer Networks, 2024 - Elsevier
Phishing attacks are a prevailing problem in cybersecurity. In many data breaches, the initial
entry can be traced back to phishing. URL-based phishing detection is one of the many …

Prompt Engineering or Fine-Tuning? A Case Study on Phishing Detection with Large Language Models

F Trad, A Chehab - Machine Learning and Knowledge Extraction, 2024 - mdpi.com
Large Language Models (LLMs) are reshaping the landscape of Machine Learning (ML)
application development. The emergence of versatile LLMs capable of undertaking a wide …

Enhancing Malicious URL Detection: A Novel Framework Leveraging Priority Coefficient and Feature Evaluation

AS Rafsanjani, NB Kamaruddin, M Behjati… - IEEE …, 2024 - ieeexplore.ieee.org
Malicious Uniform Resource Locators (URLs) pose a significant cybersecurity threat by
carrying out attacks such as phishing and malware propagation. Conventional malicious …