Detecting phishing domains using machine learning
S Alnemari, M Alshammari - Applied Sciences, 2023 - mdpi.com
Phishing is an online threat where an attacker impersonates an authentic and trustworthy
organization to obtain sensitive information from a victim. One example of such is trolling …
organization to obtain sensitive information from a victim. One example of such is trolling …
Unveiling suspicious phishing attacks: enhancing detection with an optimal feature vectorization algorithm and supervised machine learning
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 …
relatively weak anti-phishing tools, has made phishing detection a pressing challenge. In …
[HTML][HTML] Phishing websites detection using a novel multipurpose dataset and web technologies features
Phishing attacks are one of the most challenging social engineering cyberattacks due to the
large amount of entities involved in online transactions and services. In these attacks …
large amount of entities involved in online transactions and services. In these attacks …
[HTML][HTML] The applicability of a hybrid framework for automated phishing detection
Phishing attacks are a critical and escalating cybersecurity threat in the modern digital
landscape. As cybercriminals continually adapt their techniques, automated phishing …
landscape. As cybercriminals continually adapt their techniques, automated phishing …
Staying ahead of phishers: a review of recent advances and emerging methodologies in phishing detection
The escalating threat of phishing attacks poses significant challenges to cybersecurity,
necessitating innovative approaches for detection and mitigation. This paper addresses this …
necessitating innovative approaches for detection and mitigation. This paper addresses this …
Detection of adversarial phishing attack using machine learning techniques
KM Sudar, M Rohan, K Vignesh - Sādhanā, 2024 - Springer
The frequency of cyberattacks, particularly phishing attacks, is increasing exponentially
every day. Many users fall victim to clicking on malicious URLs, leading to the exploitation of …
every day. Many users fall victim to clicking on malicious URLs, leading to the exploitation of …
DaE2: Unmasking malicious URLs by leveraging diverse and efficient ensemble machine learning for online security
AE Omolara, M Alawida - Computers & Security, 2025 - Elsevier
Over 5.44 billion people now use the Internet, making it a vital part of daily life, enabling
communication, e-commerce, education, and more. However, this huge Internet connectivity …
communication, e-commerce, education, and more. However, this huge Internet connectivity …
Heuristic machine learning approaches for identifying phishing threats across web and email platforms
R Jayaprakash, K Natarajan, JA Daniel… - Frontiers in Artificial …, 2024 - frontiersin.org
Life has become more comfortable in the era of advanced technology in this cutthroat
competitive world. However, there are also emerging harmful technologies that pose a …
competitive world. However, there are also emerging harmful technologies that pose a …
PhiKitA: Phishing Kit Attacks Dataset for Phishing Websites Identification
F Castaño, EF Fernañdez, R Alaiz-Rodríguez… - IEEE …, 2023 - ieeexplore.ieee.org
Recent studies have shown that phishers are using phishing kits to deploy phishing attacks
faster, easier and more massive. Detecting phishing kits in deployed websites might help to …
faster, easier and more massive. Detecting phishing kits in deployed websites might help to …
URL based phishing attack detection using BiLSTM-gated highway attention block convolutional neural network
M Nanda, S Goel - Multimedia Tools and Applications, 2024 - Springer
Phishing is an attack that attempts to replicate the official websites of businesses, including
government agencies, financial institutions, e-commerce platforms, and banks. These …
government agencies, financial institutions, e-commerce platforms, and banks. These …