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 …
which is critical given that many of our activities are now conducted online. As a result of …
A review of computer vision methods in network security
J Zhao, R Masood, S Seneviratne - … Communications Surveys & …, 2021 - ieeexplore.ieee.org
Network security has become an area of significant importance more than ever as
highlighted by the eye-opening numbers of data breaches, attacks on critical infrastructure …
highlighted by the eye-opening numbers of data breaches, attacks on critical infrastructure …
Phishing URL detection: A real-case scenario through login URLs
M Sánchez-Paniagua, EF Fernández, E Alegre… - IEEE …, 2022 - ieeexplore.ieee.org
Phishing is a social engineering cyberattack where criminals deceive users to obtain their
credentials through a login form that submits the data to a malicious server. In this paper, we …
credentials through a login form that submits the data to a malicious server. In this paper, we …
Fuzzy rough set feature selection to enhance phishing attack detection
M Zabihimayvan, D Doran - 2019 IEEE international …, 2019 - ieeexplore.ieee.org
Phishing as one of the most well-known cybercrime activities is a deception of online users
to steal their personal or confidential information by impersonating a legitimate website …
to steal their personal or confidential information by impersonating a legitimate website …
[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 …
Combining long-term recurrent convolutional and graph convolutional networks to detect phishing sites using URL and HTML
Phishing, a well-known cyber-attack practice has gained significant research attention in the
cyber-security domain for the last two decades due to its dynamic attacking strategies …
cyber-security domain for the last two decades due to its dynamic attacking strategies …
[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 …
Phishing web page detection using N-gram features extracted from URLs
Recently, cyber-attacks have increased worldwide, especially during the pandemic period.
The number of connected devices in the world and the anonymous structure of the internet …
The number of connected devices in the world and the anonymous structure of the internet …
[PDF][PDF] Detecting phishing attacks using a combined model of LSTM and CNN
Phishing, a social engineering crime which has been existing for more than two decades,
has gained significant research attention to find better solutions to face against the very …
has gained significant research attention to find better solutions to face against the very …
It Doesn't Look Like Anything to Me: Using Diffusion Model to Subvert Visual Phishing Detectors
Visual phishing detectors rely on website logos as the invariant identity indicator to detect
phishing websites that mimic a target brand's website. Despite their promising performance …
phishing websites that mimic a target brand's website. Despite their promising performance …