Stop oversampling for class imbalance learning: A review

AS Tarawneh, AB Hassanat, GA Altarawneh… - IEEE …, 2022 - ieeexplore.ieee.org
For the last two decades, oversampling has been employed to overcome the challenge of
learning from imbalanced datasets. Many approaches to solving this challenge have been …

Analysis of the performance impact of fine-tuned machine learning model for phishing URL detection

SR Abdul Samad, S Balasubaramanian, AS Al-Kaabi… - Electronics, 2023 - mdpi.com
Phishing leverages people's tendency to share personal information online. Phishing
attacks often begin with an email and can be used for a variety of purposes. The …

An investigation into the performances of the state-of-the-art machine learning approaches for various cyber-attack detection: A survey

T Ige, C Kiekintveld, A Piplai - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
In this research, we analyzed the suitability of each of the current state-of-the-art machine
learning models for various cyberattack detection from the past 5 years with a major …

Rdpvr: Random data partitioning with voting rule for machine learning from class-imbalanced datasets

AB Hassanat, AS Tarawneh, SS Abed, GA Altarawneh… - Electronics, 2022 - mdpi.com
Since most classifiers are biased toward the dominant class, class imbalance is a
challenging problem in machine learning. The most popular approaches to solving this …

An efficient approach for phishing detection using machine learning

E Gandotra, D Gupta - Multimedia security: algorithm development …, 2021 - Springer
The increasing number of phishing attacks is one of the major concerns of security
researchers today. The traditional tools for identifying phishing websites use signature …

Detecting phishing websites using machine learning technique

AK Dutta - PloS one, 2021 - journals.plos.org
In recent years, advancements in Internet and cloud technologies have led to a significant
increase in electronic trading in which consumers make online purchases and transactions …

Multilayer stacked ensemble learning model to detect phishing websites

LR Kalabarige, RS Rao, A Abraham… - IEEE Access, 2022 - ieeexplore.ieee.org
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 …

[PDF][PDF] Website phishing detection using machine learning techniques

R Alazaidah, A Al-Shaikh… - Journal of …, 2024 - digitalcommons.aaru.edu.jo
Phishing is a cybercrime that is constantly increasing in the recent years due to the
increased use of the Internet and its applications. It is one of the most common types of …

Stock price forecasting for jordan insurance companies amid the covid-19 pandemic utilizing off-the-shelf technical analysis methods

GA Altarawneh, AB Hassanat, AS Tarawneh… - Economies, 2022 - mdpi.com
One of the most difficult problems analysts and decision-makers may face is how to improve
the forecasting and predicting of financial time series. However, several efforts were made to …

A novel phishing detection system using binary modified equilibrium optimizer for feature selection

S Minocha, B Singh - Computers & Electrical Engineering, 2022 - Elsevier
The Digital era faces security concerns due to the explosive growth of cyber-attacks, such as
phishing attacks, man-in-the-middle attacks, and many more. Phishing attackers deceive …