Results 51 to 60 of about 2,301 (212)
Fast Detection of Zero-Day Phishing Websites Using Machine Learning [PDF]
, 2022 The recent global growth in the number of internet users and online applications has led to a massive volume of personal data transactions taking place over the internet.
Nagunwa, Thomas
core
Application of Machine Learning for Real-Time Phishing Attack Detection
ITEGAM-JETIAOver the years, the Internet has been exploited to carry out a range of cyber attacks, with phishing being the most prominent one. Increasingly sophisticated techniques of phishing have threatened the security of many Internet-based systems.
Akshay Shankar Agrawal +4 more
doaj +1 more source
IET Information Security, 2023 Phishing attacks have become one of the powerful sources for cyber criminals to impose various forms of security attacks in which fake website Uniform Resource Locators (URL) are circulated around the Internet community in the form of email, messages etc.
Manoj Kumar Prabakaran +2 more
doaj +1 more source
Sufficiency of Ensemble Machine Learning Methods for Phishing Websites Detection
IEEE Access, 2022 Phishing is a kind of worldwide spread cybercrime that uses disguised websites to trick users into downloading malware or providing personally sensitive information to attackers.
Yi Wei, Yuji Sekiya
doaj +1 more source
Exploiting Vision Transformer and Ensemble Learning for Advanced Malware Classification
Engineering Reports, Volume 8, Issue 1, January 2026.Overview of the proposed RF–ViT ensemble for multi‐class malware classification. Textual (BoW/byte‐frequency) and visual representations are combined via a product rule, achieving improved accuracy and robustness over individual models. ABSTRACT Malware remains a significant concern for modern digital systems, increasing the need for reliable and ...
Fadi Makarem +4 more
wiley +1 more source
Classification of Phishing Data Using Hybrid MI-AN Feature Selection Method
مجلة بغداد للعلومWeb phishing attacks have been continually evolving over the past few years, which has led customers to lose their trust in online services and e-commerce.
Damodar Patel +3 more
doaj +1 more source
A machine learning model for predicting phishing websites
International Journal of Electrical and Computer Engineering (IJECE), 2023 There are various types of cybercrime, and hackers often target specific ones for different reasons, such as financial gain, recognition, or even revenge. Cybercrimes are not restricted by geographical boundaries and can occur globally. The prevalence of specific types of cybercrime can vary from country to country, influenced by factors such as ...
Grace Odette Boussi +2 more
openaire +1 more source
Phishing URL Detection and Interpretability With Machine Learning: A Cross‐Dataset Approach
SECURITY AND PRIVACY, Volume 9, Issue 1, January/February 2026.ABSTRACT Phishing attacks pose a significant security threat, particularly through deceptive emails designed to trick users into clicking on malicious links, with phishing URLs often serving as the primary indicator of such attacks. This paper presents a machine learning approach for detecting phishing email attacks by analyzing the URLs embedded ...
Liyan Yi +2 more
wiley +1 more source
EnLem: An Ensemble Learning-based Model for Detecting Phishing Websites
, 2023 In this paper, there is a novel model based on ensemble learning for predicting phishing websites. The overall design is a combination of three individual machine-learning models with the help of the uni-variate feature selection model for detecting ...
Zeyar Aung (17350935) +5 more
core +1 more source
Phishing and Spoofing Websites: Detection and Countermeasures [PDF]
, 2023 Website phishing and spoofing occur when unsuspecting users are tricked into interacting with a fraudulent website designed to impersonate a legitimate one. This is done with the intention of stealing login credentials or other personal information.
Lai, Wee Liem; Faculty of Engineering, Multimedia University, 63100 Cyberjaya, Malaysia +3 more
core +1 more source