Applications of deep learning for phishing detection: a systematic literature review
Phishing attacks aim to steal confidential information using sophisticated methods,
techniques, and tools such as phishing through content injection, social engineering, online …
techniques, and tools such as phishing through content injection, social engineering, online …
A new two-step ensemble learning model for improving stress prediction of automobile drivers
G Issa - The International Arab Journal of …, 2021 - research.skylineuniversity.ac.ae
Commuting when there is a significant volume of traffic congestion has been acknowledged
as one of the key factors causing stress. Significant levels of stress whilst driving are seen to …
as one of the key factors causing stress. Significant levels of stress whilst driving are seen to …
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 …
Phishing web site detection using diverse machine learning algorithms
Purpose This paper aims to present a framework to detect phishing websites using stacking
model. Phishing is a type of fraud to access users' credentials. The attackers access users' …
model. Phishing is a type of fraud to access users' credentials. The attackers access users' …
Towards benchmark datasets for machine learning based website phishing detection: An experimental study
A Hannousse, S Yahiouche - Engineering Applications of Artificial …, 2021 - Elsevier
The increasing popularity of the Internet led to a substantial growth of e-commerce.
However, such activities have main security challenges primary caused by cyberfraud and …
However, such activities have main security challenges primary caused by cyberfraud and …
Multilayer stacked ensemble learning model to detect phishing websites
Phishing is a cyber attack that tricks the online users into revealing sensitive information with
a fake website imitating a legitimate website. The attackers with stolen credentials not only …
a fake website imitating a legitimate website. The attackers with stolen credentials not only …
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 …
Application of data mining algorithms for improving stress prediction of automobile drivers: A case study in Jordan
Driving daily through traffic congestion has been recognised as a major cause of stress.
High levels of stress while driving negatively impact the driver's decisions which could …
High levels of stress while driving negatively impact the driver's decisions which could …
Study of combating technology induced fraud assault (TIFA) and possible solutions: the way forward
The study aims to identify modes of fraudulent payments and create awareness of such
incidences to avoid decisive virtual activities. Disruptive developments such as contactless …
incidences to avoid decisive virtual activities. Disruptive developments such as contactless …
Phishing website detection from URLs using classical machine learning ANN model
Phishing is a serious form of online fraud made up of spoofed websites that attempt to gain
users' sensitive information by tricking them into believing that they are visiting a legitimate …
users' sensitive information by tricking them into believing that they are visiting a legitimate …