Results 71 to 80 of about 4,265,497 (230)
Phishing Website Detection Based on Multidimensional Features Driven by Deep Learning
IEEE Access, 2019 As a crime of employing technical means to steal sensitive information of users, phishing is currently a critical threat facing the Internet, and losses due to phishing are growing steadily.
Peng Yang, Guangzhen Zhao, Peng Zeng
doaj +1 more source
Phishing Techniques in Mobile Devices
, 2018 The rapid evolution in mobile devices and communication technology has increased the number of mobile device users dramatically. The mobile device has replaced many other devices and is used to perform many tasks ranging from establishing a phone call to
Amro, Belal
core +1 more source
Expert Systems, Volume 43, Issue 3, March 2026.ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam +3 more
wiley +1 more source
Web-based phishing URL detection model using deep learning optimization techniques
International Journal of Data Science and AnalysisPhishing is a cyber-attack in which the attacker redirects Internet users to fraudulent websites. Fake websites look very similar to legitimate ones, leading users to trust them and disclose sensitive information.
Kousik Barik +2 more
semanticscholar +1 more source
A systematic literature review on phishing website detection techniques
Journal of King Saud University: Computer and Information Sciences, 2023 Phishing is a fraud attempt in which an attacker acts as a trusted person or entity to obtain sensitive information from an internet user. In this Systematic Literature Survey (SLR), different phishing detection approaches, namely Lists Based, Visual ...
Asadullah Safi, Satwinder Singh
doaj +1 more source
Predicting Phishing Websites using Neural Network trained with Back-Propagation [PDF]
, 2013 Phishing is increasing dramatically with the development of modern technologies and the global worldwide computer networks. This results in the loss of customer’s confidence in e-commerce and online banking, financial damages, and identity theft ...
McCluskey, T.L. +2 more
core
Journal of the Society for Information Display, Volume 34, Issue 2, Page 49-67, February 2026.Modern AI systems can now synthesize coherent multimedia experiences, generating video and audio directly from text prompts. These unified frameworks represent a rapid shift toward controllable and synchronized content creation. From early neural architectures to transformer and diffusion paradigms, this paper contextualizes the ongoing evolution of ...
Charles Ding, Rohan Bhowmik
wiley +1 more source
Artificial Intelligence ReviewThe escalating threat of phishing attacks poses significant challenges to cybersecurity, necessitating innovative approaches for detection and mitigation.
S. Kavya, D. Sumathi
semanticscholar +1 more source
Enhancing Phishing Email Detection through Ensemble Learning and Undersampling
Applied Sciences, 2023 In real-world scenarios, the number of phishing and benign emails is usually imbalanced, leading to traditional machine learning or deep learning algorithms being biased towards benign emails and misclassifying phishing emails.
Qinglin Qi +4 more
doaj +1 more source
Phishing or Not Phishing? A Survey on the Detection of Phishing Websites
IEEE Access, 2023 Phishing is a security threat with serious effects on individuals as well as on the targeted brands. Although this threat has been around for quite a long time, it is still very active and successful. In fact, the tactics used by attackers have been evolving continuously in the years to make the attacks more convincing and effective.
Rasha Zieni +2 more
openaire +3 more sources