The Geometry of Suspicion: Visual Exploration Patterns in Email Phishing Detection. [PDF]
Di Nocera F +5 more
europepmc +1 more source
Phishing Defense: A Machine Learning System and its Impact at Workplace
The usage of the internet and improvement in technologies have resulted in recent forms of cybercrimes that mostly affect organizations. Most common among these is phishing, a process wherein fraudsters attack through emails and websites to extract ...
Aman Poddar
core +1 more source
WebView-Based Hybrid Analysis of Link and Event for On-Device QR Phishing Detection Framework. [PDF]
Woo J, Lee S, Park I, Lee S.
europepmc +1 more source
Real-time phishing detection with AI (Presentation)
El proyecto propone un sistema de detección de phishing en tiempo real basado en inteligencia artificial, utilizando modelos de deep learning capaces de identificar patrones complejos en URLs, correos electrónicos y metadatos.
Rivera Albornoz, Vianey Estefany +1 more
core
Real-time phishing detection with AI (Poster)
El proyecto propone un sistema de detección de phishing en tiempo real basado en inteligencia artificial, utilizando modelos de deep learning capaces de identificar patrones complejos en URLs, correos electrónicos y metadatos.
Rivera Albornoz, Vianey Estefany +1 more
core
An entropy-guided hybrid framework for real-time phishing detection in digital communication systems. [PDF]
Rawat R, Rawat H, Rawat A, Rajavat A.
europepmc +1 more source
Phish Guard Phishing Website using Machine Learning Algorithms [PDF]
Phishing attacks pose a significant threat to individuals and organizations, leading to substantial financial and reputational damage. Traditional detection methods, such as blacklists and signature-based techniques, often fall short in identifying ...
Vinita, Singh +5 more
core
Hybrid MLOps framework for automated lifecycle management of adaptive phishing detection models. [PDF]
Reda A, Taie SA, Shaheen ME.
europepmc +1 more source
Phishing detection on webpages in European non-English languages based on machine learning. [PDF]
Komosny D.
europepmc +1 more source
A hybrid super learner ensemble for phishing detection on mobile devices. [PDF]
Rao RS, Kondaiah C, Pais AR, Lee B.
europepmc +1 more source

